Driving mechanism of groundwater quality and probabilistic health risk quantification in the central Yinchuan Plain.

The environmental changes from climatic, terrestrial and anthropogenic drivers can significantly influence the groundwater quality that may pose a threat to human health. However, the driving mechanism of groundwater quality and potential health risk still remains to be studied. In this paper, 165 groundwater samples were analyzed to evaluate the groundwater quality, driving mechanism, and probabilistic health risk in the central Yinchuan Plain by applying fuzzy comprehensive evaluation method (FCEM), redundance analysis (RDA) and Monte Carlo simulation. The results showed that hydrochemical evolution of groundwater were strongly influenced by water-rock interaction, evaporation and human activities. While 55.2% of groundwater samples reached the drinking water quality standard (Class I, II and III), 44.8% of samples exceeded the standard limits of Class III water quality (Class IV and V), indicating a high pollution level of groundwater. Mn, TDS, NH4+, NO3-, Fe, F-, NO2-, As were among major indicators that influence the groundwater quality due to the natural and anthropogenic processes. The RDA analysis revealed that climatic factors (PE: 10.9%, PRE: 1.1%), GE chemical properties (ORP: 20.7%, DO: 2.4%), hydrogeological factors (BD: 16.5%, K: 4.1%), and terrestrial factors (elevation: 1.2%; distanced: 5.6%, distancerl: 1.5%, NDVI: 1.2%) were identified as major driving factors influencing the groundwater quality in the study area. The HHRA suggested that TCR values of arsenic in infants, children and teens greatly exceeded the acceptable risk threshold of 1E-4, indicating a high cancer risk with a basic trend: infants > children > teens, while TCR values of adults were within the acceptable risk level. THI values of four age groups in the RME scenario were nearly ten times higher than those in the CTE scenario, displaying a great health effect on all age groups (HQ > 1). The present study provides novel insights into the driving mechanism of groundwater quality and potential health hazard in arid and semi-arid regions.

An Adaptive Trust Evaluation Model for Detecting Abnormal Nodes in Underwater Acoustic Sensor Networks.

Underwater acoustic sensor networks have a wide range of applications in both civil and military fields, but the complex and changing underwater environment makes them vulnerable to multiple security threats. Trust mechanisms are effective ways to enhance network security and reliability. In order to improve the accuracy of trust evaluation and the detection rate of abnormal nodes, this paper proposes an adaptive trust evaluation model based on fuzzy logic. This model adopts a variable weight fuzzy comprehensive evaluation algorithm to dynamically adjust the weights of three direct trust indicators to ensure the accuracy of direct trust evaluation. Then, it uses fuzzy closeness to eliminate unreliable recommendation trust and adjusts the weight of recommendation trust through deviation to improve the accuracy of indirect trust. The simulation results show that the model can effectively improve the accuracy of trust evaluation and the detection rate of abnormal nodes. Especially when the link quality is unstable, the success rate of detecting abnormal nodes in this model is improved by more than 10% compared with the existing trust model.

[Hierarchical fuzzy comprehensive evaluation of prevention and control level of occupational hazards in coal mines].

Objective: To establish an evaluation model for occupational hazard prevention and control levels in coal mines, to explore the combination of Analytic Hierarchy Process (AHP) and fuzzy comprehensive evaluation, to evaluate the overall situation of occupational hazard prevention and control in coal mines. Methods: In November 2021, Collect information of occupational hazards and their prevention and control status in 30 coal mines. AHP model was first constructed for the elements of occupational hazard prevention and control in coal mines. Then, the AHP and fuzzy comprehensive evaluation method was applied to comprehensively evaluate and grade the occupational hazard prevention and control in coal mines, using the principles of maximum membership and weighted average. Results: The hierarchical fuzzy comprehensive evaluation results for typical coal mine were basically consistent with its occupational hazard prevention and control situation. The dust prevention and control situation was good, the noise prevention and control situation is average, the occupational health monitoring situation was good, the occupational health management situation was average, and the overall level of occupational hazard prevention and control was good. Conclusion: The hierarchical fuzzy comprehensive evaluation model for occupational hazard prevention and control levels, combined with the principles of maximum membership and weighted average, can objectively evaluate and reflect the overall situation of occupational hazard prevention and control in coal mines.

A comparative evaluation of child health care in China using multicriteria decision analysis methods.

Child health is an important public health issue in China and the Chinese government always attached great importance to child health care. With the implementation of a series of medical and health reforms in China in recent decades, the status of child health improved year by year. Objectives This study aims to comprehensively evaluate if the measures implemented in the medical and health reforms effectively promoted the development of Chinese child health care in recent years and provide theoretical support for future decision-making on the policies of child health care in China. Methods A total of six indicators were selected from the China Health Statistics Yearbook. Based on the multi-criteria decision analysis (MCDA) algorithm, three different evaluation methods were applied in the study, which are the weighted technique for order preference by similarity to an ideal solution (TOPSIS) method, the weighted rank-sum ratio (RSR) method, and the fuzzy comprehensive evaluation (FCE). Each indicator's weight was calculated by the entropy weight methods objectively. The sensitivity analysis was conducted to validate the stability and accuracy of the rank results. Results The results indicated that the rank values of each year's child health care calculated by the different evaluation methods were not exactly the same, but the overall trend is consistent which is that child health care in China improved year by year from 2000 to 2020. The top 5 were ranked from 2016-2020 and the bottom 5 were ranked from 2000-2004. Conclusions The results indicated that the policies and measures implemented in the medical and health reforms, as well as improved sanitation conditions, availability of healthy food and water, etc., have jointly promoted the development of child health care in China in the past 20 years, providing a scientific theoretical basis for future policy-making to promote child health care.

Development of a multicriteria decision-making model for evaluating hybrid offspring in the sweetpotato (Ipomoea batatas L.) breeding process.

Sweetpotato variety breeding is always a long process. Screening of hybrid offspring is dominated by empirical judgment in this process. Data analysis and decision fatigue have been troubling breeders. In recent years, the low-efficiency screening mode has been unable to meet the requirements of sweetpotato germplasm innovation. Therefore, it is necessary to construct a high-efficiency method that can screen germplasms for different usages, for mining elite genotypes, and to create dedicated sweetpotato varieties. In this article, the multicriteria decision-making (MCDM) model was constructed based on six agronomic traits, including fresh root yield, vine length, vine diameter, branch number, root number and the spatial distribution of storage roots, and five quality traits, including dry matter content, marketable root yield, uniformity of roots, starch content and the edible quality score. Among these, the edible quality score was calculated by using fuzzy comprehensive evaluation to integrate the sensory scores of color, odor, sweetness, stickiness and fibrous taste. The MCDM model was compared with the traditional screening method via an evaluation in 25 sweetpotato materials. The interference of subjective factors on the evaluation results was significantly reduced. The MCDM model is more overall, more accurate and faster than the traditional screening method in the selection of elite sweetpotato materials. It could be programmed to serve the breeders in combination with the traditional screening method.

Fuzzy comprehensive evaluation with AHP and entropy methods and health risk assessment of groundwater in Yinchuan Basin, northwest China.

Water quality evaluation and health risk assessment are not only the basis of environmental protection work, but also of great significance to water environment supervision and management. In this paper, the fuzzy comprehensive evaluation for water quality was improved by using the analytic hierarchy process (AHP) and Entropy, and a health risk assessment model based on triangular fuzzy theory was developed. The evaluation results show 5 water categories: Class-1 (n = 1, 2%), Class-2 (n = 14, 32%), Class-3 (n = 15, 34%), Class-4 (n = 8, 18%) and Class-5 (n = 6, 14%), manifesting about 67% of the phreatic water can be used for drinking purposes in the research area. The Chadha diagram provides hydrochemical facies of the phreatic water are mainly NaCl type (n = 16, 36%) and Ca-Mg-Na type (n = 15, 34%). Fluorine as non-carcinogenic factor in health risk assessment, showing moderate correlation with SO42- (r = 0.54) and low correlation with Na+ (r = 0.38) in Pearson correlation analysis. The order of non-carcinogenic risk per year is as follow: Class-2, Class-3, All, Class-4 and Class-5 with the mean of 0.29, 0.51, 0.67, 0.86 and 1.55 × 10-8 for adults, 0.54, 0.95, 1.27, 1.58 and 2.89 × 10-8 for children. Compare with adults, children undertake higher health risk, in research area. Particularly, the region accepting Class-5 water supplement encounter high non-carcinogenic risk, where risk level is 2.24 and 2.28 times to the average risk level for adults and children, respectively. This paper provides insights into solving uncertainties in groundwater management and environmental protection, as well as into fuzzy logic techniques addressing pollution.

[Screening methods of traditional Chinese medicine for coronary heart disease and angina pectoris: an exploration based on core outcome set and fuzzy comprehensive evaluation].

It was pointed out in Opinions on Promoting the Inheritance, Innovation and Development of Traditional Chinese Medicine issued by the State Council in 2019 that 100 varieties of traditional Chinese medicine(TCM) with unique curative effects should be screened out within about three years. Due to the multi-component and multi-target mechanisms of TCM varieties, it is difficult to directly and simply evaluate their multi-dimensional clinical value using methods applicable to chemical or biological agents. The heterogeneity of outcomes for similar TCM makes it difficult to determine the advantages of similar products. The fuzzy comprehensive evaluation method that is developed on the basis of core outcome set and fuzzy mathematics for clinical efficacy evaluation of TCM may solve these problems. This study developed a fuzzy comprehensive evaluation model for the clinical efficacy evaluation of Chinese patent me-dicines for coronary heart disease and angina pectoris, and selected the previous normative studies with complete or incomplete data for verifying the model application. The results showed that original studies with complete data failed to evaluate and compare the comprehensive efficacy of different interventions. The original research only mentioned the advantages and disadvantages of different interventions in different aspects. The comprehensive clinical efficacy of three different interventions obtained through fuzzy comprehensive evaluation was all graded as level Ⅱ. The original research with incomplete data drew the same conclusions as the fuzzy comprehensive evaluation, and the results of fuzzy comprehensive evaluation can provide more comprehensive information. Therefore, the fuzzy comprehensive evaluation shows the products with overall advantages of clinical efficacy, which may become a feasible method for the screening of TCM.

A Novel Location Source Optimization Algorithm for Low Anchor Node Density Wireless Sensor Networks.

Location information is one of the basic elements of the Internet of Things (IoT), which is also an important research direction in the application of wireless sensor networks (WSNs). Aiming at addressing the TOA positioning problem in the low anchor node density deployment environment, the traditional cooperative localization method will reduce the positioning accuracy due to excessive redundant information. In this regard, this paper proposes a location source optimization algorithm based on fuzzy comprehensive evaluation. First, each node calculates its own time-position distribute conditional posterior Cramer-Rao lower bound (DCPCRLB) and transfers it to neighbor nodes. Then collect the DCPCRLB, distance measurement, azimuth angle and other information from neighboring nodes to form a fuzzy evaluation factor set and determine the final preferred location source after fuzzy change. The simulation results show that the method proposed in this paper has better positioning accuracy about 33.9% with the compared method in low anchor node density scenarios when the computational complexity is comparable.

Flood Risk Assessment and Regionalization from Past and Future Perspectives at Basin Scale.

Flooding is a major natural disaster that has brought tremendous losses to mankind throughout the ages. Even so, floods can be controlled by appropriate measures to minimize loss and damage. Flood risk assessment is an essential analytic step in preventing floods and reducing losses. Identifying previous flood risk and predicting future features are conducive to understanding the changing patterns and laws of flood risk. Taking the Dongjiang River basin as a study case, we assessed and regionalized flood risk in 1990, 2000, and 2010 from the past perspective and explored dynamic expansion during 1990-2010. Then, we projected land-use type, population, and gross domestic product in 2030 and 2050 and finally assessed and regionalized the risk from a future perspective. Results show that areas with very high risk accounted for 14.98-18.08% during 1990-2010; approximately 13.90% areas of the basin transformed from lower-level risk to higher-level risk whereas 9.07% fell from a higher level to a lower level during the period. For the future scenario, areas with very high and high risk in 2030 and 2050 are expected to account for 21.55% and 24.84%, respectively. Generally, our study can better identify changes in flood risk at a spatial scale and reveal the dynamic evolution rule, which provides a synthetical means of flood prevention and reduction, flood insurance, urban planning, and water resource management in the future under global climate change, especially for developing or high-speed urbanization regions.

Evaluating the CO2 geological storage suitability of coal-bearing sedimentary basins in China.

The geological storage of CO2 is potentially one of the most effective methods to reduce the CO2 concentration in the atmosphere. Coalbeds are possibly suitable storage reservoirs, meaning that evaluating the suitability of individual coalbeds and associated engineering and construction is an important step in developing geological CO2 storage. This evaluation requires the development of a reasonable evaluation index system and associated weightings. This paper focuses on coal-bearing basins in China and outlines a technical process whereby the CO2 storage suitability of these basins can be comprehensively evaluated. This study uses an earth system science approach to determine the uncertainties involved in identifying ideal CO2 storage sites, develops an index that outlines the conditions related to the suitability of Chinese coal-bearing basins for geological CO2 storage, and incorporates this index into a hierarchical index system model for geological CO2 storage suitability that allows the comprehensive evaluation of coal-bearing basins and includes 5 aspects, 23 indexes, and 5 index levels. The weighting assigned to each evaluation index was determined using the analytic hierarchy process (AHP) and was subsequently incorporated into a fuzzy logic-based comprehensive evaluation approach. This approach was applied to assess the suitability of the Qinshui Basin for geological CO2 storage, revealing that this basin is indeed a suitable coalbed reservoir. The comprehensive geological CO2 storage evaluation model outlined here can also assess the CO2 storage suitability and capacity of other coal-bearing basins elsewhere in China and globally.

Assessment of ecological environment impact in highway construction activities with improved group AHP-FCE approach in China.

Highway construction is time consuming and complicated. Various environmental issues can be encountered during this process. Therefore, it is necessary to assess the impact of ecologic environment in highway construction. However, the traditional assessment approaches paid more attention to the environmental factors rather than the ecological problems, and the weights of evaluation indexes were assigned with relatively average values, which cannot comprehensively and accurately to assess the impact of ecological environment in highway construction. In order to solve these problems, this paper established a new model to combine improved group AHP and FCE. A total of six main factors and 22 sub-factors from three aspects of social, ecological, and natural environment were identified. The model and index system were applied to the ecological environment impact assessment of the highway from the city of Hanzhong to Lueyang County section in Shaanxi Province, and compared with traditional fuzzy AHP approach to verify the feasibility of this model. The results showed that only the ranking of social and ecological factor changed when comparing with the traditional approach. The weight of social factor determined by the improved approach was 0.2835, while that of the traditional approach was only 0.2365, and the weight difference was 0.047. This improved approach highlighted the importance of social factor and overcame the equal weight distribution of traditional approach, which made the overall weight ratio distribution more reasonable and objective. The comprehensive assessment result was 0.3482, which was in line with the "general impact" level. This was consistent with the actual situation of highway construction. The improved group AHP-FCE model could be used successfully for assessing the impact of the ecological environment in highway construction, and it had good applicability and popularization value in ecological environment assessment.

Multiple flood vulnerability assessment approach based on fuzzy comprehensive evaluation method and coordinated development degree model.

Flood is a serious challenge that increasingly affects the residents as well as policymakers. Flood vulnerability assessment is becoming gradually relevant in the world. The purpose of this study is to develop an approach to reveal the relationship between exposure, sensitivity and adaptive capacity for better flood vulnerability assessment, based on the fuzzy comprehensive evaluation method (FCEM) and coordinated development degree model (CDDM). The approach is organized into three parts: establishment of index system, assessment of exposure, sensitivity and adaptive capacity, and multiple flood vulnerability assessment. Hydrodynamic model and statistical data are employed for the establishment of index system; FCEM is used to evaluate exposure, sensitivity and adaptive capacity; and CDDM is applied to express the relationship of the three components of vulnerability. Six multiple flood vulnerability types and four levels are proposed to assess flood vulnerability from multiple perspectives. Then the approach is applied to assess the spatiality of flood vulnerability in Hainan's eastern area, China. Based on the results of multiple flood vulnerability, a decision-making process for rational allocation of limited resources is proposed and applied to the study area. The study shows that multiple flood vulnerability assessment can evaluate vulnerability more completely, and help decision makers learn more information about making decisions in a more comprehensive way. In summary, this study provides a new way for flood vulnerability assessment and disaster prevention decision.

A new air quality monitoring and early warning system: Air quality assessment and air pollutant concentration prediction.

Air pollution in many countries is worsening with industrialization and urbanization, resulting in climate change and affecting people's health, thus, making the work of policymakers more difficult. It is therefore both urgent and necessary to establish amore scientific air quality monitoring and early warning system to evaluate the degree of air pollution objectively, and predict pollutant concentrations accurately. However, the integration of air quality assessment and air pollutant concentration prediction to establish an air quality system is not common. In this paper, we propose a new air quality monitoring and early warning system, including an assessment module and forecasting module. In the air quality assessment module, fuzzy comprehensive evaluation is used to determine the main pollutants and evaluate the degree of air pollution more scientifically. In the air pollutant concentration prediction module, a novel hybridization model combining complementary ensemble empirical mode decomposition, a modified cuckoo search and differential evolution algorithm, and an Elman neural network, is proposed to improve the forecasting accuracy of six main air pollutant concentrations. To verify the effectiveness of this system, pollutant data for two cities in China are used. The result of the fuzzy comprehensive evaluation shows that the major air pollutants in Xi'an and Jinan are PM10 and PM2.5 respectively, and that the air quality of Xi'an is better than that of Jinan. The forecasting results indicate that the proposed hybrid model is remarkably superior to all benchmark models on account of its higher prediction accuracy and stability.

Risk assessment of supply chain for pharmaceutical excipients with AHP-fuzzy comprehensive evaluation.

As the essential components in formulations, pharmaceutical excipients directly affect the safety, efficacy, and stability of drugs. Recently, safety incidents of pharmaceutical excipients posing seriously threats to the patients highlight the necessity of controlling the potential risks. Hence, it is indispensable for the industry to establish an effective risk assessment system of supply chain. In this study, an AHP-fuzzy comprehensive evaluation model was developed based on the analytic hierarchy process and fuzzy mathematical theory, which quantitatively assessed the risks of supply chain. Taking polysorbate 80 as the example for model analysis, it was concluded that polysorbate 80 for injection use is a high-risk ingredient in the supply chain compared to that for oral use to achieve safety application in clinic, thus measures should be taken to control and minimize those risks.

Risk assessment of supply chain for pharmaceutical excipients with AHP-fuzzy comprehensive evaluation.

As the essential components in formulations, pharmaceutical excipients directly affect the safety, efficacy, and stability of drugs. Recently, safety incidents of pharmaceutical excipients posing seriously threats to the patients highlight the necessity of controlling the potential risks. Hence, it is indispensable for the industry to establish an effective risk assessment system of supply chain. In this study, an AHP-fuzzy comprehensive evaluation model was developed based on the analytic hierarchy process and fuzzy mathematical theory, which quantitatively assessed the risks of supply chain. Taking polysorbate 80 as the example for model analysis, it was concluded that polysorbate 80 for injection use is a high-risk ingredient in the supply chain compared to that for oral use to achieve safety application in clinic, thus measures should be taken to control and minimize those risks.

Water quality assessment in Qu River based on fuzzy water pollution index method.

A fuzzy improved water pollution index was proposed based on fuzzy inference system and water pollution index. This method can not only give a comprehensive water quality rank, but also describe the water quality situation with a quantitative value, which is convenient for the water quality comparison between the same ranks. This proposed method is used to assess water quality of Qu River in Sichuan, China. Data used in the assessment were collected from four monitoring stations from 2006 to 2010. The assessment results show that Qu River water quality presents a downward trend and the overall water quality in 2010 is the worst. The spatial variation indicates that water quality of Nanbashequ section is the pessimal. For the sake of comparison, fuzzy comprehensive evaluation and grey relational method were also employed to assess water quality of Qu River. The comparisons of these three approaches' assessment results show that the proposed method is reliable.

Urban flood risk warning under rapid urbanization.

In the past decades, China has observed rapid urbanization, the nation's urban population reached 50% in 2000, and is still in steady increase. Rapid urbanization in China has an adverse impact on urban hydrological processes, particularly in increasing the urban flood risks and causing serious urban flooding losses. Urban flooding also increases health risks such as causing epidemic disease break out, polluting drinking water and damaging the living environment. In the highly urbanized area, non-engineering measurement is the main way for managing urban flood risk, such as flood risk warning. There is no mature method and pilot study for urban flood risk warning, the purpose of this study is to propose the urban flood risk warning method for the rapidly urbanized Chinese cities. This paper first presented an urban flood forecasting model, which produces urban flood inundation index for urban flood risk warning. The model has 5 modules. The drainage system and grid dividing module divides the whole city terrain into drainage systems according to its first-order river system, and delineates the drainage system into grids based on the spatial structure with irregular gridding technique; the precipitation assimilation module assimilates precipitation for every grids which is used as the model input, which could either be the radar based precipitation estimation or interpolated one from rain gauges; runoff production module classifies the surface into pervious and impervious surface, and employs different methods to calculate the runoff respectively; surface runoff routing module routes the surface runoff and determines the inundation index. The routing on surface grid is calculated according to the two dimensional shallow water unsteady flow algorithm, the routing on land channel and special channel is calculated according to the one dimensional unsteady flow algorithm. This paper then proposed the urban flood risk warning method that is called DPSIR model based multiple index fuzzy evaluation warning method, and referred to as DMFEW method. DMFEW first selects 5 evaluation indexes based on the DPSIR model for flood risk warning evaluation, including driving force index, pressure index, state index, impact index and response index. Based on the values of all evaluation indexes, one evaluation index for the whole system evaluation result is determined by using the fuzzy comprehensive evaluation method. The flood risk level is divided into 4 levels, having Level 1 the most serious. Every evaluation index is also categorized as 4 levels, and a linear fuzzy subjection function is proposed to do the fuzzy comprehensive evaluation. Dongguan City is used as the study case to validate the proposed method. The urban flood forecasting model is set up with the topographic data, the city map, the underground pipelines and land cover types, and two flood events are simulated with observed precipitation, one is interpolated from the rain gauges data, and another is estimated by digital weather radar. The simulated results are compared with the investigated water depth, and the results show the model has very good performances. The results are further used for the flood risk warning simulation, and are very reasonable.

Towards efficient and accurate prediction of freeway accident severity using two-level fuzzy comprehensive evaluation.

Accurately predicting freeway accident severity is crucial for accident prevention, road safety, and emergency rescue services in intelligent freeway systems. However, current research lacks the required precision, hindering the effective implementation of freeway rescue. In this paper, we efficiently address this challenge by categorizing influencing factors into two levels: human and non-human, further subdivided into 6 and 36 categories, respectively. Furthermore, based on the above factors, an efficient and accurate Freeway Accident Severity Prediction (FASP) method is developed by using the two-level fuzzy comprehensive evaluation. The factor and evaluation sets are determined by calculating the fuzzy evaluation matrix of a single factor. The weight matrix is calculated through the entropy method to compute the final evaluation matrix. Based on the maximum membership principle, the severity of the freeway accident is predicted. Finally, based on the experiments conducted with the traffic accident datasets in China and the US, it is shown that FASP is able to accurately predict the severity of freeway traffic accidents with thorough considerations and low computational cost. It is noted that FASP is the first attempt to achieve freeway accident severity prediction using the two-level fuzzy comprehensive evaluation method to the best of our knowledge.

A comprehensive assessment of environmental factors in aircraft cockpit based on fuzzy evaluation.

BACKGROUND: The cockpit of an aircraft is the main place where the pilot controls the aircraft on a mission. An excellent cockpit environment not only ensures the pilot's basic survival needs but also improves the comfort level and alleviates fatigue when performing missions. OBJECTIVE: On the basis of domestic and international airworthiness standards, a top-down refinement method is deployed to determine the initial goal, and the environmental criteria are fully discussed and balanced in a dynamic process to build a comprehensive evaluation system for environmental factors in the aircraft cockpit. METHODS: Based on the fuzzy comprehensive evaluation theory, an evaluation model for environmental factors is constructed by combining analytic hierarchical analysis (AHP) and particle swarm optimization (PSO). Then the feasibility of the evaluation model is verified by an illustrative example. RESULTS: The results suggest that the light environment gains the highest score among the 4 environmental criteria followed by the thermal environment, while both sound environment and microenvironment have relatively low scores. CONCLUSION: As for the 27 environmental sub-criteria, temperature, illumination, lighting clarity, light-color coordination, noise duration and pressure score the highest. The evaluation findings can provide important environmental control criteria for the subsequent environmental control system in the cockpit of the aircraft.

Quantitative assessment of human motion for health and rehabilitation: A novel fuzzy comprehensive evaluation approach.

In the pursuit of advancing health and rehabilitation, the quintessence of human motion recognition technology has been underscored through its quantitative contributions to physical performance assessment. This research delineates the inception of a novel fuzzy comprehensive evaluation-based recognition method that stands at the forefront of such innovative endeavours. By synergistically fusing multi-sensor data and advanced classification algorithms, the proposed system offers a granular quantitative analysis with implications for health and fitness monitoring, particularly rehabilitation processes. Our methodological approach, grounded in the modal separation technique and Empirical Mode Decomposition (EMD), effectively distills the motion acceleration component from raw accelerometer data, facilitating the extraction of intricate motion patterns. Quantitative analysis revealed that our integrated framework significantly amplifies the accuracy of motion recognition, achieving an overall recognition rate of 90.03 %, markedly surpassing conventional methods, such as Support Vector Machines (SVM), Decision Trees (DT), and K-Nearest Neighbors (KNN), which hovered around 80 %. Moreover, the system demonstrated an unprecedented accuracy of 97 % in discerning minor left-right swaying motions, showcasing its robustness in evaluating subtle movement nuances-a paramount feature for rehabilitation and patient monitoring. This marked precision in motion recognition heralds a new paradigm in health assessment, enabling objective and scalable analysis pertinent to individualized therapeutic interventions. The experimental evaluation accentuates the system's adeptness at navigating the dichotomy between complex, intense motions and finer, subtler movements with a high fidelity rate. It substantiates the method's utility in delivering sophisticated, data-driven insights for rehabilitation trajectory monitoring.