Powertrain Matching and Optimization of Dual-Motor Hybrid Driving System for Electric Vehicle Based on Quantum Genetic Intelligent Algorithm by Yong Wang, Dongye Sun

“…Based on preliminary matches, quantum genetic algorithm was introduced to optimize the matching in the dual-motor hybrid power system. …”
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Application of Soft Computing Techniques for the Analysis of Tractive Properties of a Low-Power Agricultural Tractor under Various Soil Conditions by Katarzyna Pentoś, Krzysztof Pieczarka, Krzysztof Lejman

“…To this end, the performances of soft computing approaches, including neural networks, genetic algorithms, and adaptive network fuzzy inference system, were evaluated. …”
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Research on the optimization of drum structure based on virtual prototyping technology by Xin Jin, Dongpo Han, Guochao Zhao, Lijuan Zhao, Hongmei Liu

“…By fitting the comprehensive performance evaluation function of the drum, the optimal structural parameters are obtained through the improved Non-Dominated Sorting Genetic Algorithms (NSGA-II). Taking into account both technical and economic factors, the optimal helix angle is ultimately determined to be 18°, the optimal installation angle is 45°, and the optimal cutting distance is 71 mm. …”
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PSO Based PI Controller Design for a Solar Charger System by Her-Terng Yau, Chih-Jer Lin, Qin-Cheng Liang

“…According to the simulation and experimental results, the control parameters resulted from PSO have better performance than genetic algorithms (GAs).…”
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Feature Extraction and Selection Scheme for Intelligent Engine Fault Diagnosis Based on 2DNMF, Mutual Information, and NSGA-II by Peng-yuan Liu, Bing Li, Cui-e Han, Feng Wang

“…A novel feature extraction and selection scheme is presented for intelligent engine fault diagnosis by utilizing two-dimensional nonnegative matrix factorization (2DNMF), mutual information, and nondominated sorting genetic algorithms II (NSGA-II). Experiments are conducted on an engine test rig, in which eight different engine operating conditions including one normal condition and seven fault conditions are simulated, to evaluate the presented feature extraction and selection scheme. …”
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Feature Selection and Parameter Optimization of Support Vector Machines Based on Modified Cat Swarm Optimization by Kuan-Cheng Lin, Yi-Hung Huang, Jason C. Hung, Yung-Tso Lin

“…Previous studies have indicated that CSO algorithms outperform other well-known metaheuristics, such as genetic algorithms and particle swarm optimization. This study presents a modified version of cat swarm optimization (MCSO), capable of improving search efficiency within the problem space. …”
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Toward Enhancing the Energy Efficiency and Minimizing the SLA Violations in Cloud Data Centers by E. I. Elsedimy, Fahad Algarni

“…VMPMOPSO was compared with a simple single-objective algorithm, called First-Fit-Decreasing (FFD), and two multiobjective ant colony and genetic algorithms. Two simulation experiments were conducted to verify the effectiveness and efficiency of the proposed VMPMOPSO. …”
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Optimizing cut order planning: A comparative study of heuristics, metaheuristics, and MILP algorithms by Sharif Al-Mahmud, Jose Alejandro Cano, Emiro Antonio Campo, Stephan Weyers

“…Modifications to existing heuristics, combined with tournament selection in genetic algorithms (GA), improve solution quality and efficiency. …”
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Advanced Ai Tools for Predicting Mechanical Properties of Self-Compacting Concrete by AGRAWAL Achal, CHANDAK Narayan

“…The present study utilizes advanced numerical evaluation techniques like Artificial Intelligence (AI), including Support Vector Machines (SVM), Artificial Neural Networks (ANN), Adaptive Neuro-Fuzzy Inference Systems with Genetic Algorithms (ANFIS-GA), Gene Expression Programming (GEP), and Multiple Linear Regression (MLR) to develop and compare the predictive models for determination of compressive and tensile strength. …”
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Non-linear multi-objective optimization model of production planning based on fuzzy logic and machine learning by Zahra Saeidi Mobarakeh, Hossein Amoozadkhalili

“…This model uses the combination of non-dominant fourth sorting genetic algorithms (NSGA-IV) and variable selection network (VSN) in a hybrid framework and provides an advanced and multi-faceted approach to solving complex multi-objective optimization problems. …”
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Evaluation of novel NaOH/activated carbon/zeolite biocomposite as an efficient adsorbent for oilfield produced water treatment by Eghe Amenze Oyedoh, Onyedikachi Praise Igbokwe

“…The adsorption process was optimized using Response Surface Methodology (RSM) and Artificial Neural Networks (ANN) integrated with genetic algorithms. The results indicated a hydrocarbon removal efficiency of 99.86 % with RSM and 99.99 % with ANN under optimal conditions. …”
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Optimal capacity planning with economic emission considerations in isolated solar-wind-diesel microgrid using combined arithmetic-golden jackal optimization by Sujoy Barua, Adel Merabet, Ahmed Al-Durra, Tarek El Fouly, Ehab F. El-Saadany

“…The results demonstrate significant cost savings using the solar-wind-diesel microgrid under the proposed combined optimization compared to the arithmetic optimization algorithm and golden jackal algorithm and conventional metaheuristic optimization based on genetic algorithms.…”
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A Survey of Nature-Inspired Meta-Heuristic Algorithms in Network Alignment by Anagh Awal, Farsuram Pandit

“…It explores a wide range of nature-inspired algorithms, including genetic algorithms, particle swarm optimization, ant colony optimization, and simulated annealing. …”
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RL-QPSO net: deep reinforcement learning-enhanced QPSO for efficient mobile robot path planning by Yang Jing, Li Weiya

“…Traditional path planning methods such as genetic algorithms, Dijkstra's algorithm, and Floyd's algorithm typically rely on deterministic search strategies, which can lead to local optima and lack global search capabilities in dynamic settings. …”
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Control of Discrete Event Systems by Means of Discrete Optimization and Disjunctive Colored PNs: Application to Manufacturing Facilities by Juan-Ignacio Latorre-Biel, Emilio Jiménez-Macías, Mercedes Pérez de la Parte, Julio Blanco-Fernández, Eduardo Martínez-Cámara

“…Furthermore, the metaheuristic of genetic algorithms is applied to the search of the best solutions in the solution space. …”
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Deep Learning-Based Home Energy Management Incorporating Vehicle-to-Home and Home-to-Vehicle Technologies for Renewable Integration by Marwan Mahmoud, Sami Ben Slama

“…By utilizing data from a Tunisian weather database, smart cities significantly reduce electricity costs compared to traditional energy management methods, such as Dynamic Programming (DP), Rule-Based Systems, and Genetic Algorithms. The system’s performance is validated through robust AI models, performance metrics, and simulation scenarios, which test the system’s effectiveness under various energy demand patterns and changing weather conditions. …”
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Optimization and loss estimation in energy-deficient polygeneration systems: A case study of Pakistan's utilities with integrated renewable energy by Muhammad Shoaib Saleem, Naeem Abas

“…Techniques used for electricity demand forecasting encompass artificial intelligence, artificial neural networks, trend line extrapolations, fuzzy logic, vector support machines, genetic algorithms and expert systems. Demand forecasting becomes even more difficult in polygeneration utilities with renewable energy sources integrated to meet the varying demands. …”
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Introducing a Markov Chain-Based Energy Awareness Approach for Cloud Data Center Virtual Machine Dynamic Management by Xinbin Huang, Yu Huang, Cecılıa. Mercado

“…The approach integrates genetic algorithms and refrigeration simulation into the migration replacement process, leveraging absorbing Markov chains for predictive analysis. …”
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A Data Fusion System for Simulation of Critical Scenarios and Decision-Making by Jimmy Anderson Flórez Zuluaga, Esteban Patiño Carrasco, Jose David Ortega Pabón, Kelly Gallego León, O. Lucía Quintero Montoya

“…This document describes an investigation product resulted in a simulation system, based on a combination of fuzzy logic, genetic algorithms and decision trees which let modelled and simulated various entities and their automatic response according to simulated patterns and situations, in which, through operators, decision maker can modify entities behaviour, according to parameterized restrictions and physical conditions. …”
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Genetic Artificial Hummingbird Algorithm-Support Vector Machine for Timely Power Theft Detection by Emmanuel Gbafore, Davies Rene Segera, Cosmas Raymond Mutugi Kiruki

“…The proposed algorithm combines the artificial hummingbird algorithm exploration phase with the genetic algorithm’s mutation and crossover operators, to optimize the support vector machine’s hyperparameters and categorize users as fraudulent or nonfraudulent. …”
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