Artificial intelligence for waste management in smart cities: a review
B Fang, J Yu, Z Chen, AI Osman, M Farghali… - Environmental …, 2023 - Springer
The rising amount of waste generated worldwide is inducing issues of pollution, waste
management, and recycling, calling for new strategies to improve the waste ecosystem, such …
management, and recycling, calling for new strategies to improve the waste ecosystem, such …
Intelligent approaches for sustainable management and valorisation of food waste
Food waste (FW) is a severe environmental and social concern that today's civilization is
facing. Therefore, it is necessary to have an efficient and sustainable solution for managing …
facing. Therefore, it is necessary to have an efficient and sustainable solution for managing …
Plant-scale biogas production prediction based on multiple hybrid machine learning technique
The parameters from full-scale biogas plants are highly nonlinear and imbalanced, resulting
in low prediction accuracy when using traditional machine learning algorithms. In this study …
in low prediction accuracy when using traditional machine learning algorithms. In this study …
Application of machine learning and genetic algorithms to the prediction and optimization of biodiesel yield from waste cooking oil
The synthesis and usage of biodiesel have become the focus of extensive research due to
the ever-increasing emphasis on the development of sustainable and renewable sources …
the ever-increasing emphasis on the development of sustainable and renewable sources …
A comprehensive review of digital twin technology for grid-connected microgrid systems: State of the art, potential and challenges faced
The concept of the digital twin has been adopted as an important aspect in digital
transformation of power systems. Although the notion of the digital twin is not new, its …
transformation of power systems. Although the notion of the digital twin is not new, its …
Enhancing waste cooking oil biodiesel yield and characteristics through machine learning, response surface methodology, and genetic algorithms for optimal …
The current study seeks to predict and optimize the biodiesel production yield and
physicochemical properties of waste cooking oil. Using Box-Behnken design (BBD), L46 …
physicochemical properties of waste cooking oil. Using Box-Behnken design (BBD), L46 …
Comparing the effect of mesophilic and thermophilic anaerobic co-digestion for sustainable biogas production: An experimental and recurrent neural network model …
Anaerobic digestion is a promising technology for treating bio wastes from energetic and
environmental point of views. Co-digestion of wastes and process temperature are essential …
environmental point of views. Co-digestion of wastes and process temperature are essential …
Securing China's rice harvest: unveiling dominant factors in production using multi-source data and hybrid machine learning models
Ensuring the security of China's rice harvest is imperative for sustainable food production.
The existing study addresses a critical need by employing a comprehensive approach that …
The existing study addresses a critical need by employing a comprehensive approach that …
Enhanced detoxification methods for the safe reuse of treated olive mill wastewater in irrigation
R Alrowais, RS Yousef, O Ahmed… - Environmental Sciences …, 2023 - Springer
Abstract Olive Mill Wastewater (OMWW) is produced in large quantities and contains high
levels of nutrients that can be reused for irrigation, reducing the demand for freshwater …
levels of nutrients that can be reused for irrigation, reducing the demand for freshwater …
Smart investigation of artificial intelligence in renewable energy system technologies by natural language processing: Insightful pattern for decision-makers
K Niroomand, NMC Saady, C Bazan… - … Applications of Artificial …, 2023 - Elsevier
This study aims to provide a framework which enables decision-makers and researchers to
identify AI technology patterns in renewable energy systems from a massive data set of …
identify AI technology patterns in renewable energy systems from a massive data set of …