Assessment of inorganic solid waste management techniques using full consistency and extended MABAC method.

Population and industrial growth have spiked product consumption, which in turn have caused an abrupt rise in municipal solid waste (MSW) production. Due to the lack of resources allocated to waste management, municipal inorganic solid waste (ISW) has increased exponentially, posing a significant strain on the environment and health. To mitigate these issues, sustainable waste management strategies need to be implemented to reduce environmental impacts and improve waste collection and disposal efficiency. The objective of our work was to analyse and identify the most effective techniques for disposing of ISW in India by employing multi-criteria decision-making (MCDM). This technique entails selecting the most suitable alternative based on a variety of competing and interactive criteria. A fusion decision model named the FULL COnsistency Method (FUCOM) and Multi-Attributive Border Approximation area Comparison (MABAC) based on the interval-valued q-rung orthopair fuzzy (IV q-ROF) was developed. Finally, a comparative analysis was performed to demonstrate the system's robustness.

Sustainable assessment of plastic and mixed waste disposal problem during COVID-19 pandemic: an integrated multi-criteria decision-making approach.

This article focuses on India's inorganic solid waste disposal problem, with a particular emphasis on plastic and mixed waste. It aims to identify the current COVID-19 pandemic situation as well as provide a suitable disposal technique for wastes that are specifically related to municipal solid waste management. We propose an integrated approach to disposing of paper and plastic and mixed wastes in an interval-valued q-rung orthopair fuzzy (IVq-ROF) environment for this problem. In this case, we use the FUCOM method to calculate the weight values of the criteria and the MABAC method to rank the alternatives based on the chosen criteria. To confirm the effectiveness of the proposed method, a numerical illustration is provided, and validation of the suggested method is also shown.

Knowledge-based normative safety measure approach: systematic assessment of capabilities to conquer COVID-19.

In this research article, we have introduced a knowledge-based approach to regional/national security measures. Proposed Knowledge-based Normative Safety Measure algorithm for safety measures helps to take practical actions to conquer COVID-19. We analyzed based on five dimensions: the correlation between detected cases and confirmed cases, social distance, the speed of detected cases, the correlation between imported cases and inbound cases, and the proportion of masks worn. It prompts actions based on the security level of the region. Through the use of our proposed algorithm, the government has accelerated the implementation of social distancing, accelerated test cases, and policies, etc., to prevent people from contracting COVID-19. This idea can be a very effective way to realize the impending danger and take action in advance. Help speed up the process of controlling the COVID-19. In pandemic times, it can be helpful to understand better. Holding the normative safety measure at a high level leads nations to perform excellently on triple T's (testing, tracking, and treatment) policy and other safety acts. The proposed NSM approach facilitates for improve the governance of cities and communities.

Dynamics of fractional order nonlinear system: A realistic perception with neutrosophic fuzzy number and Allee effect.

Introduction: The fusion of fractional order differential equations and fuzzy numbers has been widely used in modelling different engineering and applied sciences problems. In addition to these, the Allee effect, which is of high importance in field of biology and ecology, has also shown great contribution among other fields of sciences to study the correlation between density and the mean fitness of the subject. Objectives: The present paper is intended to measure uncertain dynamics of an economy by restructuring the Cobb-Douglas paradigm of the renowned Solow-Swan model. The purpose of study is further boosted innovatively by subsuming the perception of logistic growth with Allee effect in the dynamics of physical capital and labor force. Methods: Fractional order derivative and neutrosophic fuzzy (NF) theory are applied on the parameters of the Cobb-Douglas equation. Distinctively, cogitating fractional order derivative to study the change at each fractional stage; single-valued triangular neutrosophic fuzzy numbers (SVTNFN) to cope the uncertain situations; logistic growth function with Allee effect to analyze the factors in natural way, are the significant and novel features of this endeavor. Results: The incorporation of the aforementioned theories and effects in the Cobb-Douglas equation, resulted in producing maximum sustainable capital investment and maximum capacity of labor force. The solutions in intervals located different possible solutions for different membership degrees, which accumulated the uncertain circumstances of a country. Conclusion: Explicitly, these notions add new facts and figures not only in the dynamical study of capital and labor, which has been overlooked in classical models, but also left the door open for discussion and implementation on classical models of different fields.