Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 20 de 12.164
Filtrar
1.
Artigo em Inglês | MEDLINE | ID: mdl-36166200

RESUMO

OBJECTIVE: COVID-19 disrupted public transit and led to increased reliance on alternative modes of transportation (AMTs) internationally. This study hypothesizes that public interest and fracture injuries associated with AMTs increased during COVID-19 in the United States. METHODS: Monthly Google search probabilities and the number of fracture injuries associated with bicycles, scooters, skateboards/longboards, rollerblades, electric bicycles, and electric micromobility vehicles were collected from January 2017 to December 2021. Wilcoxon signed-rank tests were used to assess differences in search probabilities and fracture injuries between 2021, 2020, and 2019. Linear regression was used to study the relationship between search probabilities and number of fracture injuries. RESULTS: For bicycles, skateboards/longboards, electric bicycles, and electric micromobility vehicles, search probabilities and fracture injuries were higher in 2021 and 2020 compared with 2019, except for bicycle fractures in 2021 (P < 0.05). For every AMT, except roller skates, search probability had an explanatory effect on fracture injuries (P < 0.001). CONCLUSION: Online interest in AMTs and associated fracture injuries increased during the COVID-19 pandemic. Excess fractures seem to be stabilizing as of December 2021, but online search volumes may be used to inform the allocation of orthopaedic trauma resources during future surges in COVID-19 and other epidemics.


Assuntos
COVID-19 , Fraturas Ósseas , COVID-19/epidemiologia , Eletricidade , Fraturas Ósseas/epidemiologia , Fraturas Ósseas/etiologia , Humanos , Pandemias , Meios de Transporte , Estados Unidos/epidemiologia
2.
Part Fibre Toxicol ; 19(1): 61, 2022 09 15.
Artigo em Inglês | MEDLINE | ID: mdl-36109745

RESUMO

BACKGROUND: Exposure to air pollutants is one of the major environmental health risks faced by populations globally. Information about inhaled particle deposition dose is crucial in establishing the dose-response function for assessing health-related effects due to exposure to air pollution. OBJECTIVE: This study aims to quantify the respiratory tract deposition (RTD) of equivalent black carbon (BC) particles in healthy young adults during a real-world commuting scenario, analyze factors affecting RTD of BC, and provide key parameters for the assessment of RTD. METHODS: A novel in situ method was applied to experimentally determine the RTD of BC particles among subjects in the highly polluted megacity of Metro Manila, Philippines. Exposure measurements were made for 40 volunteers during public transport and walking. RESULTS: The observed BC exposure concentration was up to 17-times higher than in developed regions. The deposition dose rate (DDR) of BC was up to 3 times higher during commute inside a public transport compared to walking (11.6 versus 4.4 µg hr-1, respectively). This is twice higher than reported in similar studies. The average BC mass deposition fraction (DF) was found to be 43 ± 16%, which can in large be described by individual factors and does not depend on gender. CONCLUSIONS: Commuting by open-sided public transport, commonly used in developing regions, poses a significant health risk due to acquiring extremely high doses of carcinogenic traffic-related pollutants. There is an urgent need to drastically update air pollution mitigation strategies for reduction of dangerously high emissions of BC in urban setting in developing regions. The presented mobile measurement set-up to determine respiratory tract deposition dose is a practical and cost-effective tool that can be used to investigate respiratory deposition in challenging environments.


Assuntos
Poluentes Atmosféricos , Emissões de Veículos , Poluentes Atmosféricos/análise , Poluentes Atmosféricos/toxicidade , Carbono , Humanos , Filipinas , Sistema Respiratório , Fuligem/análise , Fuligem/toxicidade , Meios de Transporte , Emissões de Veículos/análise , Emissões de Veículos/toxicidade , Adulto Jovem
3.
Artigo em Inglês | MEDLINE | ID: mdl-36078510

RESUMO

The Retail Food Environment Index (RFEI) and its variants have been widely used in public health to measure people's accessibility to healthy food. These indices are purely environmental as they only concern the geographic distribution of food retailers, but fail to include human factors, such as demographics, socio-economy, and mobility, which also shape the food environment. The exclusion of human factors limits the explanatory power of RFEIs in identifying neighborhoods of the greatest concern. In this study, we first proposed a hybrid approach to integrate human and environmental factors into the RFEI. We then demonstrated this approach by incorporating neighborhood commuting patterns into a traditional RFEI: we devised a multi-origin RFEI (MO_RFEI) that allows people to access food from both homes and workplaces, and further an enhanced RFEI (eRFEI) that allows people to access food with different transportation modes. We compared the traditional and proposed RFEIs in a case study of Florida, USA, and found that the eRFEI identified fewer and more clustered underserved populations, allowing policymakers to intervene more effectively. The eRFEI depicts more realistic human shopping behaviors and better represents the food environment. Our study enriches the literature by offering a new and generic approach for assimilating a neighborhood context into food environment measures.


Assuntos
Comércio , Características de Residência , Alimentos , Abastecimento de Alimentos , Humanos , Meios de Transporte
4.
Artigo em Inglês | MEDLINE | ID: mdl-36078535

RESUMO

To a certain degree, the resilience of the transportation system expresses the safety of the transportation system, because it reflects the ability of the system to maintain its function in the face of disturbance events. In the current research, the assessment of the resilience of urban mobility is attractive and challenging. Apart from this, the concept of green mobility has been popular in recent years. As a representative way of shared mobility, the implementation of ridesharing will affect the level of urban mobility resilience to a certain extent. In this paper, we use a data low-intensity method to evaluate the urban traffic resilience under the circumstance of restricted car use. In addition, we incorporate the impact of ridesharing services. The research in this paper can be regarded as an evaluation framework, which can help policy makers and relevant operators to grasp the overall resilience characteristics of cities in emergencies, identify weak sectors, and formulate the best response plan. This method has been successfully applied to two cities in China, demonstrating its potential for practice. Finally, we also explored the relationship between urban traffic resilience and the pattern of population distribution. The analysis shows that population density has an impact on the level of transportation resilience. And the incorporation of ridesharing will bring an obvious increment in resilience of most areas.


Assuntos
Meios de Transporte , China , Cidades , Densidade Demográfica
5.
Artigo em Inglês | MEDLINE | ID: mdl-36078573

RESUMO

Active commuting to school (ACS) seems to be one of the means to increase physical activity (PA) levels in youth, but it is unclear if ACS reduces the prevalence of obesity, protecting and improving their health. Most of the previous research has been conducted on children or youth (i.e., children with adolescents together), and there is a paucity of research in adolescents only. The purpose of this review was to assess the association between ACS with overweight/obesity parameters in adolescents aged 11 to 19 years. We used PubMed, WOS and SPORTDiscus as electronics databases. All steps of the process followed the recommendations of the PRISMA flow-diagram. Fifteen articles (68.18%) found a consistent association between ACS and body composition and seven studies (31.82%) showed no differences in body composition between active and passive commuters to school. Fourteen studies observed that active commuters to school had a more favorable body composition and one study reported that ACS was associated with unfavourable body composition. ACS could be the steppingstone to improve PA promotion in adolescence but whether ACS is associated with improved body composition and prevention of obesity requires further research.


Assuntos
Obesidade Pediátrica , Adolescente , Ciclismo , Criança , Humanos , Sobrepeso , Obesidade Pediátrica/epidemiologia , Obesidade Pediátrica/prevenção & controle , Prevalência , Instituições Acadêmicas , Meios de Transporte , Caminhada
6.
Artigo em Inglês | MEDLINE | ID: mdl-36078710

RESUMO

In order to solve the problems of improper order allocation and the lack of a carbon emission constraint system in the road freight transportation industry, this paper proposed an order allocation mechanism of network freight transportation with carbon tax constraints and established an order allocation optimization model with carbon tax constraints. Based on the basic characteristics of the problem, this paper redesigns the ant colony labor division expansion model, and designs a corresponding algorithm to solve the problem. By improving the update rules of the stimulus value and the threshold value, the matching difference between the order and the driver of the network freight platform is enlarged, and the matching relation-ship is dynamically adjusted, the order allocation scheme is optimized, and a more appropriate carbon tax rate range in this industry is explored. Furthermore, the problem is solved by a 0-1 integer programming algorithm, which is compared with the algorithm designed in this paper. Through multiple numerical simulation experiments, the effectiveness and feasibility of the algorithm are verified. The experimental results show that the order allocation arrangement of the online freight platform with carbon tax constraints is more economical and environmentally friendly.


Assuntos
Algoritmos , Carbono , Carbono/análise , Indústrias , Políticas , Meios de Transporte
7.
PLoS One ; 17(9): e0274632, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-36099261

RESUMO

An essential consideration in urban transit facility planning is service efficiency and accessibility. Previous research has shown that reducing the number of facilities along a route may increase efficiency but decrease accessibility. Striking a balance between these two is a critical consideration in transit planning. Transit facility consolidation is a cost-effective way to improve the quality of service by strategically determining the desirable allocation of a limited number of facilities. This paper develops an optimization framework that integrates Geographical Information systems (GIS), decision-making analysis, and quantum technologies for addressing the problem of facility consolidation. Our proposed framework includes a novel mathematical model that captures non-linear interactions between facilities and surrounding demand nodes, inter-facility competition, ridership demand and spatial coverage. The developed model can harness the power of quantum effects such as superposition and quantum tunnelling and enables transportation planners to utilize the most recent hardware solutions such as quantum and digital annealers, coherent Ising Machines and gate-based universal quantum computers. This study presents a real-world application of the framework to the public transit facility redundancy problem in the British Columbia Vancouver metropolitan area. We demonstrate the effectiveness of our framework by reducing the number of facilities by 40% while maintaining the same service accessibility. Additionally, we showcase the ability of the proposed mathematical model to take advantage of quantum annealing and classical optimization techniques.


Assuntos
Sistemas de Informação Geográfica , Acesso aos Serviços de Saúde , Colúmbia Britânica , Modelos Teóricos , Meios de Transporte
8.
Front Public Health ; 10: 1013421, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-36172205

RESUMO

E-bike, characterized as a low-carbon and health-beneficial active travel mode, is gradually becoming popular in China. Although built environment factors are considered to be key parameters that can facilitate or hinder active transportation, such as cycling or walking, few studies have explored the impact of built environment on e-bikes. To fill this gap, this study was the first to explore the relationship between e-bike usage and built environment factors based on population level travel survey in central Jinan, China. Both macro and micro levels of built environment were measured using multi-source data. We employed ordinary least squares (OLS) and geographically weighted regression (GWR) models to explore the aggregation patterns of e-bike trips. Besides, the local Moran's I was employed to classify the aggregation patterns of e-bike trips into four types. The results from OLS model showed that eye-level greenery, building floor area, road density and public service POI were positive significantly related to e-bike trips, while open sky index and NDVI had negative association with e-bike trips. The usage of GWR model provided more subtle results, which revealed significant spatial heterogeneity on the impacts of different built environment parameters. Road density and public service POI posed positive effects on e-bike travel while NDVI and open sky index were found mainly pose negative impacts on e-bike travel. Moreover, we found similar coefficient distribution patterns of eye-level greenery, building floor area and distance to bus stop. Therefore, tailored planning interventions and policies can be developed to facilitate e-bike travel and promote individual's health level.


Assuntos
Ciclismo , Ambiente Construído , Carbono , China , Humanos , Meios de Transporte/métodos
9.
Comput Intell Neurosci ; 2022: 1608167, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-36172323

RESUMO

The application of Internet of Things technology in cold chain transportation can greatly strengthen the monitoring of all aspects of cold chain logistics, so as to promote the progress of cold chain logistics industry. In order to study this aspect, this paper chooses the key link of the Internet of Things as a breakthrough. By analyzing various aspects of the transportation process, an Internet of Things middleware framework serving cold chain transportation tracking is designed. The main products of logistics cold chain transportation are fresh agricultural products, so in order to further make the research fit the actual situation, this paper collects the logistics data and information of agricultural products through investigation and combines the core technology of agricultural products logistics with the Internet and the key technology of cold chain transportation to process the obtained information. The analytic hierarchy process and fuzzy comprehensive evaluation method are used in this process. The processing results prove the validity and rationality of the established index system. The purpose of developing the international trade management system is to enable the company to optimize its international trade management process, reduce some tedious and inconvenient manual operations, make the recording and statistics of international trade information very simple, improve work efficiency, and satisfy the information needs of various departments to enable enterprises to minimize costs, thereby enabling enterprises to obtain better economic benefits.


Assuntos
Comércio , Refrigeração , Algoritmos , Internacionalidade , Meios de Transporte
10.
Artigo em Inglês | MEDLINE | ID: mdl-36142039

RESUMO

The development of traffic infrastructure involves massive land use changes along the transportation routes and stimulates urban sprawl at transfer nodes, leading to a degradation in ecosystem services, including soil conservation. For developing countries, especially for China, it is very important to differentiate the influences between different standards of traffic infrastructure associated with the different administrative levels of the regions where they are constructed on soil conservation. In this study, we attempt to analyze the differences in the influence of accessibility at different levels on soil conservation, for the case study area in Hunan province in China. The results indicate that: (1) traffic conditions in Hunan province have witnessed continuous improvement, and the time taken to access mega-cities, prefecture-level cities, and county-level cities from various regions has been significantly reduced. (2) The total annual soil conservation in Hunan province is maintained at approximately 2.93 × 109 t. However, the spatial heterogeneity shows severe degradation in regions with lower accessibility, and weak enhancement in regions with higher accessibility. (3) A negative spatial autocorrelationship exists between accessibility and soil conservation at all levels, with the increase of administrative rank of the destination making it more obvious and intense, along with an increased tendency for the spatial distribution to concentrate. (4) Building more railways and highways from prefecture-level cities with LH clusters nearby as transfer nodes, instead of the construction of national roads and provincial roads that diverge from these railways and highways, will help limit the massive expansion of construction land and soil erosion within prefecture-level cities, rather than spreading to towns of LH clusters. This research provides an important scientific basis for future regional planning and traffic infrastructure construction, and also a reference for traffic infrastructure development in other geographically similar regions on a synchronous development stage in the world.


Assuntos
Ecossistema , Solo , China , Cidades , Conservação dos Recursos Naturais , Meios de Transporte
11.
Sci Rep ; 12(1): 15988, 2022 Sep 26.
Artigo em Inglês | MEDLINE | ID: mdl-36163340

RESUMO

Understanding human mobility is of great significance for sustainable transportation planning. Long-term travel delay change is a key metric to measure human mobility evolution in cities. However, it is challenging to quantify the long-term travel delay because it happens in different modalities, e.g., subway, taxi, bus, and personal cars, with implicated coupling. More importantly, the data for long-term multi-modal delay modeling is challenging to obtain in practice. As a result, the existing travel delay measurements mainly focus on either single-modal system or short-term mobility patterns, which cannot reveal the long-term travel dynamics and the impact among multi-modal systems. In this paper, we perform a travel delay measurement study to quantify and understand long-term multi-modal travel delay. Our measurement study utilizes a 5-year dataset of 8 million residents from 2013 to 2017 including a subway system with 3 million daily passengers, a 15 thousand taxi system, a 10 thousand personal car system, and a 13 thousand bus system in the Chinese city Shenzhen. We share new observations as follows: (1) the aboveground system has a higher delay increase overall than that of the underground system but the increase of it is slow down; (2) the underground system infrastructure upgrades decreases the aboveground system travel delay increase in contrast to the increase the underground system travel delay caused by the aboveground system infrastructure upgrades; (3) the travel delays of the underground system decreases in the higher population region and during the peak hours.


Assuntos
Meios de Transporte , Viagem , Automóveis , Cidades , Humanos , Estudos Longitudinais
12.
Sci Rep ; 12(1): 16120, 2022 Sep 27.
Artigo em Inglês | MEDLINE | ID: mdl-36167963

RESUMO

Nowadays, Transit-Oriented Development (TOD) plays a vital role for public transport planners in developing potential city facilities. Knowing the necessity of this concept indicates that TOD effective parameters such as network accessibility (node value) and station-area land use (place value) should be considered in city development projects. To manage the coordination between these two factors, we need to consider ridership and peak and off-peak hours as essential enablers in our investigations. To aim this, we conducted our research on Chengdu rail-transit stations as a case study to propose our Node-Place-Ridership-Time (NPRT) model. We applied the Multiple Linear Regression (MLR) to examine the impacts of node value and place value on ridership. Finally, K-Means and Cube Methods were used to classify the stations based on the NPRT model results. This research indicates that our NPRT model could provide accurate results compared with the previous models to evaluate rail-transit stations.


Assuntos
Meios de Transporte , Cidades , Meios de Transporte/métodos
13.
Environ Sci Pollut Res Int ; 29(47): 70746-70771, 2022 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-36057064

RESUMO

The negative externalities of freight transport have caught the attention of scholars and practitioners to study sustainable freight transportation. Past studies have reviewed sustainable logistics from varying perspectives, but the rail mode-specific sustainable logistics has not been thoroughly reviewed. This sets the motivation to review existing research on sustainable rail freight transportation (SRFT). A science mapping approach was used to develop and visualize bibliographic networks of 378 articles published between 2001 and 2022 and indexed in the Scopus database. Four scientometric analysis techniques, namely journal co-citations; countries/organizations/authors co-authorship; document co-citations; and keywords co-occurrence, were employed in the VOSviewer software to reveal conceptual structure, social structure, and influential themes of the SRFT domain. Based on the results, the SRFT knowledge was categorized into six thematic branches (31 sub-branches), namely intermodal transportation for decarbonization; green policies, risk, and energy assessment research; savings in externalities for a sustainable future; decision-making with environmental and economic considerations; case studies and applications in SRFT research; and technological advancements towards sustainability. Finally, future research directions were proposed in the form of research questions. This systematic literature review will facilitate the researchers, practitioners, and policymakers to understand the status quo, existing research gaps, and emerging research topics in the SRFT research domain. This study is restricted to research articles and review articles published in English and indexed in the Scopus database.


Assuntos
Ferrovias , Meios de Transporte , Meios de Transporte/métodos
14.
PLoS One ; 17(9): e0273904, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-36083876

RESUMO

In this article, we construct an international oligopoly that explicitly incorporates transporter behavior. In each country, there is one firm that produces differentiated goods and invests in product-differentiating R&D and one transporter that transports the differentiated goods. We adopt a three-stage game in which the firms decide their R&D investment level to determine the degree of horizontal differentiation, the transporters determine the transportation prices through Cournot competition, and then the firms determine the quantities of production. We find that an increase in R&D efficiency in the product differentiation of firms leads to a decrease in transportation prices. We also reveal that an increase in the efficiency of product differentiation always reduces the profits of firms. These results explain the empirically plausible long-term trend of declining transportation prices and also provide a counterintuitive implication that efficiency gains reduce the degree of product differentiation.


Assuntos
Investimentos em Saúde , Meios de Transporte
15.
Sensors (Basel) ; 22(17)2022 Aug 25.
Artigo em Inglês | MEDLINE | ID: mdl-36080882

RESUMO

The state monitoring of the railway track line is one of the important tasks to ensure the safety of the railway transportation system. While the defect recognition result, that is, the inspection report, is the main basis for the maintenance decision. Most previous attempts have proposed intelligent detection methods to achieve rapid and accurate inspection of the safety state of the railway track line. However, there are few investigations on the automatic generation of inspection reports. Fortunately, inspired by the recent advances and successes in dense captioning, such technologies can be investigated and used to generate textual information on the type, position, status, and interrelationship of the key components from the field images. To this end, based on the work of DenseCap, a railway track line image captioning model (RTLCap for short) is proposed, which replaces VGG16 with ResNet-50-FPN as the backbone of the model to extract more powerful image features. In addition, towards the problems of object occlusion and category imbalance in the field images, Soft-NMS and Focal Loss are applied in RTLCap to promote defect description performance. After that, to improve the image processing speed of RTLCap and reduce the complexity of the model, a reconstructed RTLCap model named Faster RTLCap is presented with the help of YOLOv3. In the encoder part, a multi-level regional feature localization, mapping, and fusion module (MFLMF) are proposed to extract regional features, and an SPP (Spatial Pyramid Pooling) layer is employed after MFLMF to reduce model parameters. As for the decoder part, a stacked LSTM is adopted as the language model for better language representation learning. Both quantitative and qualitative experimental results demonstrate the effectiveness of the proposed methods.


Assuntos
Processamento de Imagem Assistida por Computador , Meios de Transporte , Cognição , Processamento de Imagem Assistida por Computador/métodos , Idioma , Reconhecimento Psicológico
16.
Sensors (Basel) ; 22(17)2022 Aug 26.
Artigo em Inglês | MEDLINE | ID: mdl-36080912

RESUMO

Transportation Mode Detection (TMD) is an important task for the Intelligent Transportation System (ITS) and Lifelog. TMD, using smartphone built-in sensors, can be a low-cost and effective solution. In recent years, many studies have focused on TMD, yet they support a limited number of modes and do not consider similar transportation modes and holding places, limiting further applications. In this paper, we propose a new network framework to realize TMD, which combines structural and spatial interaction features, and considers the weights of multiple sensors' contributions, enabling the recognition of eight transportation modes with four similar transportation modes and four holding places. First, raw data is segmented and transformed into a spectrum image and then ResNet and Vision Transformers (Vit) are used to extract structural and spatial interaction features, respectively. To consider the contribution of different sensors, the weights of each sensor are recalibrated using an ECA module. Finally, Multi-Layer Perceptron (MLP) is introduced to fuse these two different kinds of features. The performance of the proposed method is evaluated on the public Sussex-Huawei Locomotion-Transportation (SHL) dataset, and is found to outperform the baselines by at least 10%.


Assuntos
Redes Neurais de Computação , Smartphone , Meios de Transporte
17.
Sensors (Basel) ; 22(17)2022 Aug 29.
Artigo em Inglês | MEDLINE | ID: mdl-36080971

RESUMO

The correlations between smartphone sensors, algorithms, and relevant techniques are major components facilitating indoor localization and tracking in the absence of communication and localization standards. A major research gap can be noted in terms of explaining the connections between these components to clarify the impacts and issues of models meant for indoor localization and tracking. In this paper, we comprehensively study the smartphone sensors, algorithms, and techniques that can support indoor localization and tracking without the need for any additional hardware or specific infrastructure. Reviews and comparisons detail the strengths and limitations of each component, following which we propose a handheld-device-based indoor localization with zero infrastructure (HDIZI) approach to connect the abovementioned components in a balanced manner. The sensors are the input source, while the algorithms are used as engines in an optimal manner, in order to produce a robust localizing and tracking model without requiring any further infrastructure. The proposed framework makes indoor and outdoor navigation more user-friendly, and is cost-effective for researchers working with embedded sensors in handheld devices, enabling technologies for Industry 4.0 and beyond. We conducted experiments using data collected from two different sites with five smartphones as an initial work. The data were sampled at 10 Hz for a duration of five seconds at fixed locations; furthermore, data were also collected while moving, allowing for analysis based on user stepping behavior and speed across multiple paths. We leveraged the capabilities of smartphones, through efficient implementation and the optimal integration of algorithms, in order to overcome the inherent limitations. Hence, the proposed HDIZI is expected to outperform approaches proposed in previous studies, helping researchers to deal with sensors for the purposes of indoor navigation-in terms of either positioning or tracking-for use in various fields, such as healthcare, transportation, environmental monitoring, or disaster situations.


Assuntos
Algoritmos , Smartphone , Computadores , Meios de Transporte
18.
Sensors (Basel) ; 22(17)2022 Sep 05.
Artigo em Inglês | MEDLINE | ID: mdl-36081169

RESUMO

In recent years, with the development of science and technology, people have more and more choices for daily travel. However, assisting with various mobile intelligent services by transportation mode detection has become more urgent for the refinement of human activity identification. Although much work has been done on transportation mode detection, accurate and reliable transportation mode detection remains challenging. In this paper, we propose a novel transportation mode detection algorithm, namely T2Trans, based on a temporal convolutional network (i.e., TCN), which employs multiple lightweight sensors integrated into a phone. The feature representation learning of multiple preprocessed sensor data using temporal convolutional networks can improve transportation mode detection accuracy and enhance learning efficiency. Extensive experimental results demonstrated that our algorithm attains a macro F1-score of 86.42% on the real-world SHL dataset and 88.37% on the HTC dataset, with an average accuracy of 86.37% on the SHL dataset and 89.13% on the HTC dataset. Our model can better identify eight transportation modes, including stationary, walking, running, cycling, car, bus, subway, and train, with better transportation mode detection accuracy, and outperform other benchmark algorithms.


Assuntos
Smartphone , Caminhada , Algoritmos , Ciclismo , Atividades Humanas , Humanos , Meios de Transporte
20.
Comput Intell Neurosci ; 2022: 7934582, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-36093495

RESUMO

Logistics is the transfer of goods from one place to another, mostly from the production house to the customers. A logistics network is a set of operations that involve designing, production, and marketing the goods. Cold-chain logistics are those that needed to be transported in a cold refrigeration right from the production house to the customer. A secured networking model is essential to handle the logistics networks. In this article, we are going to see an intelligent secured networking model to identify the optimal path for cold-chain logistics to hospitals. The optimal pathfinder is used to find the path between point A to point B, which is short and best. It also considers the road traffic and cost of transport. The cold-chain logistics to the hospitals include medicines and vaccines, which are to be stored at a particular temperature. Thus, path optimization is more essential in cold-chain logistics to hospitals than other types of logistics. In this research, the bee-ant optimization algorithm (BAOA) is proposed to perform the intelligent transportation to the hospitals. The proposed algorithm is compared with the existing ant colony optimization (ACO), bee colony optimization (BCO), and neural network model. From the results, it can be observed that the proposed algorithm shows 98.83% for the accurate delivery of logistics to the hospitals.


Assuntos
Algoritmos , Inteligência Artificial , Animais , Abelhas , Atenção à Saúde , Meios de Transporte
SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA
...