Genetic research
Researchers at the University of Tehran in Iran have developed a novel folding light shelf system that integrates reflectors, photovoltaic (PV) modules, and adaptive louvers to improve daylight distribution, minimize glare, and reduce energy consumption in office buildings. The system uses an advanced optimization approach, Non-dominated Sorting Genetic Algorithm III
Genetic research
Researchers from the University of Science and Technology of China have developed a genetic algorithm-based energy management strategy for fuel cell hybrid electric vehicles. This strategy, designed to minimize the overall operating cost of the system, involves establishing dynamic and static models of the hydrogen-electric hybrid vehicle, as well as
Genetic research
Researchers from the National University of Defense Technology in Changsha, People's Republic of China, have developed an improved genetic algorithm-based path planning model designed to minimize total travel distance while respecting vehicle capacity constraints. The model has been tested on four benchmark maps from the Carla simulation platform,
Genetic research
Researchers at the Universidad Nacional de Chimborazo have successfully applied a hybrid genetic algorithm-neural network approach to optimize the dosage of polyaluminum chloride (PAC) in drinking water treatment, leading to significant cost savings and improved water quality compliance. The study, published in the journal Computation, utilized operational data from 400
Machine learning
Researchers at Marwadi University have developed a method to optimize the placement and sizing of distributed generations (DGs) and shunt capacitors in power distribution networks. By utilizing renewable energy resources, such as photovoltaic cells and wind turbines, the study aims to ensure a specific level of reliability in power distribution
Machine learning
Researchers from Imam Mohammad Ibn Saud Islamic University have made significant contributions to sustainable land management by developing a novel integration of the Ninja Optimization Algorithm (NiOA) for simultaneous feature selection and hyperparameter optimization. This innovative approach enables accurate prediction of soil organic carbon (SOC) levels, which play a crucial
Machine learning
Research published in the journal Discover Artificial Intelligence highlights the application of long short-term memory (LSTM) networks and simulated annealing algorithms in smart rural construction and college students' skill entrepreneurship. The study explores the potential of these algorithms in predicting key indicators for crop growth and agricultural market fluctuations,
Genetic research
A team of researchers from Xi'an Jiaotong University has made significant progress in the development and optimization of a biodiesel-methanol mechanism using a genetic algorithm. The research, conducted by Ying Wang and her team, aimed to create a more accurate and realistic model for predicting the behavior of
Algorithms
Researchers at Erciyes University have proposed a new approach to improving the performance of metaheuristic algorithms using reinforcement learning-based acceptance criteria. The study, published in the International Journal of Computational Intelligence Systems, found that metaheuristics with deep Q-learning-based offline acceptance criteria outperformed existing acceptance criteria and other variants. This breakthrough
Genetic research
Research from the University of Florida has demonstrated the efficacy of utilizing artificial intelligence (AI) in estimating lake volumes without the need for bathymetric data. This innovative approach employs the Google Earth Engine platform, AI, and genetic algorithms to analyze water surface areas and estimate lake volume. The method was
Machine learning
A recent study published in the journal Energy Informatics has shed light on the development of next-generation intelligent sensor networks. Researchers from the School of Electrical Engineering have presented a Particle Swarm Optimization (PSO) algorithm, which optimizes the deployment of electronic information sensing nodes to maximize monitored area while minimizing
Genetic research
Researchers from Nanjing University of Aeronautics and Astronautics, in collaboration with colleagues from other institutions, have developed a novel artificial intelligence (AI)-driven approach to two-dimensional irregular pattern packing. This method integrates advanced image processing with an enhanced Genetic Algorithm (GA) to improve material utilization and compactness of pattern placement.
