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Home»Science»Transforming Plastic Waste into a Sustainable Future: An AI-Powered Recycling Solution
Science

Transforming Plastic Waste into a Sustainable Future: An AI-Powered Recycling Solution

November 2, 2024No Comments5 Mins Read
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Plastic pollution has become a global environmental crisis, with billions of tons of plastic waste accumulating in our oceans and landfills. However, a team of researchers has developed a groundbreaking solution that combines artificial intelligence (AI) and advanced decision-making techniques to revolutionize plastic recycling. This innovative approach, using a bipolar dual hesitant fuzzy set, offers a promising way to tackle the plastic waste problem and pave the way for a more sustainable future. By evaluating various plastic recycling methods, the researchers have identified the optimal techniques that can maximize environmental, economic, and social benefits. This research holds the potential to transform the way we manage plastic waste, leading to a cleaner, greener, and more circular economy.

Tackling the Plastic Pollution Crisis

Plastic has become an integral part of our modern lives, offering convenience, durability, and versatility. However, the widespread use and improper disposal of plastic materials have led to a global environmental crisis. Plastic waste, which can take hundreds or even thousands of years to decompose, is accumulating in landfills, oceans, and ecosystems, causing severe damage to ecosystems and biodiversity. The release of harmful chemicals and the emission of greenhouse gases during the degradation of plastic further exacerbate the problem, contributing to climate change and environmental degradation.

Harnessing the Power of Artificial Intelligence

To address this pressing issue, a team of researchers has developed an innovative approach that combines decisionanalysis’>multi-criteria decision-making (MCDM) framework, the researchers have systematically evaluated these alternatives based on four key criteria: environment, economics, social and technical factors, and safety.

Table 2 Literature review of ELECTRE method and bipolar hesitant fuzzy set.

Identifying the Optimal Recycling Technique

The researchers have utilized the ELECTRE (Elimination and Choice Expressing Reality) method, a renowned MCDM approach, to rank the plastic recycling alternatives. The bipolar dual hesitant fuzzy ELECTRE (BDHF-ELECTRE) technique has enabled the researchers to handle the inherent uncertainties and ambiguities in the decision-making process. Through this comprehensive analysis, the researchers have determined that mechanical recycling emerges as the most efficient and versatile plastic recycling method, considering the various environmental, economic, social, and safety factors.

Unlocking the Potential of Sustainable Plastic Waste Management

The findings of this research hold significant implications for the future of plastic waste management. By identifying the optimal recycling technique, the researchers have provided a roadmap for policymakers, waste management authorities, and industry stakeholders to implement more effective and sustainable plastic recycling programs. This approach not only reduces the environmental impact of plastic waste but also promotes resource conservation, energy efficiency, and overall cost-effectiveness in managing plastic waste.

Towards a Circular Economy

The successful implementation of the BDHF-ELECTRE technique in plastic recycling aligns with the principles of a Click Here

This article is made freely available to the public under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. This license allows anyone to share, distribute, and reproduce the content in any medium or format, as long as they give proper credit to the original author(s) and the source, and provide a link to the license. However, you are not permitted to make any adaptations or derivative works from this article or its parts. The images or other third-party material included in this article are also covered by the same Creative Commons license, unless otherwise stated. If you wish to use the material in a way that is not allowed by the license or exceeds the permitted use, you will need to obtain direct permission from the copyright holder.
Aerospace Sustainability agricultural waste management Artificial intelligence bipolar dual hesitant fuzzy sets circular economy ELECTRE environmental protection multi-criteria decision-making plastic recycling resource conservation
jeffbinu
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Tech enthusiast by profession, passionate blogger by choice. When I'm not immersed in the world of technology, you'll find me crafting and sharing content on this blog. Here, I explore my diverse interests and insights, turning my free time into an opportunity to connect with like-minded readers.

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