Improving Performance of the Convolutional Neural Networks for Electricity Theft Detection by using Cheetah Optimization Algorithm by Hassan Ghaedi, Seyed Reza Kamel Tabbakh, Reza Ghaemi

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Application of bioinspired global optimization algorithms to the improvement of the prediction accuracy of compact extreme learning machines by L. A. Demidova, A. V. Gorchakov

“…By adjusting input weights with bioinspired optimization algorithms, it was shown that the prediction accuracy of ELMs in regression problems can be improved to reduce the number of hidden-layer neurons to reach a high prediction accuracy on learning and test datasets. …”
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An improved meta-heuristic algorithm to optimize the fractional-order controller for an industrial manipulator with a parallelogram structure by Nazila Nikdel

“…Numerical results show the satisfying performances of the proposed controller and the improved optimization algorithm.…”
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Structural Simulation Model Updating Based on Improved MCMC Algorithm and Surrogate Model by MIAO Ji, DUAN Liping, LIU Jiming, LIN Siwei, ZHAO Jincheng

“…The results show that WOA can significantly improve the stability and convergence speed of the MCMC algorithm, the updating efficiency can be improved by 13.9% at most, and the maximum frequency errors of the simply supported beam model and the three-story steel frame model updated by the WO-MH algorithm are 0.009% and 2.41%, respectively. …”
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Multi-objective Optimization Configuration of Capacitor Blocking Devices Based on Field-Circuit Coupled Model and Improved Differential Evolution Algorithm by Hongwei LIU

“…Based on the operating characteristics of the DC blocking devices, this paper analyzes the influence of the DC blocking devices on the DC current near the neutral point of the transformers, and proposes a multi-objective optimization configuration method for capacitor blocking devices based on the field-circuit coupling model and improved differential evolution algorithm. …”
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Air Quality Prediction Using Neural Networks with Improved Particle Swarm Optimization by Juxiang Zhu, Zhaoliang Zhang, Wei Gu, Chen Zhang, Jinghua Xu, Peng Li

“…Second, the inertia weights and learning factors of the standard PSO are improved to ensure the global search ability exhibited by the algorithm in the early stage and the ability to rapidly obtain the optimal solution in the later stage; we also introduce an adaptive variation algorithm in the particle search process to prevent the particles from being caught in local optima. …”
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An Adaptive Fusion Path Tracking Strategy for Autonomous Vehicles Based on Improved ACO Algorithm by Jihan Zhang, Yuan Wang, Jinyan Hu, Hongwu You

“…Although methods based on dynamic models and optimization theory can improve tracking performance, most autonomous systems lack high-fidelity models and the complexity of optimization processes lead to increase computational burden. …”
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Improving kinetic model fitting for total titratable acidity in bananas using genetic algorithms by Alejandro Kevin Méndez Castillo, Elizabeth Contreras López, Jesús Guadalupe Pérez Flores, Laura García Curiel, Emmanuel Pérez Escalante, Karla Soto Vega, Carlos Ángel-Jijón, Alicia Cervantes Elizarrarás

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Hybrid stochastic and robust optimization of a hybrid system with fuel cell for building electrification using an improved arithmetic optimization algorithm by Fude Duan, Mahdiyeh Eslami, Mustafa Okati, Dheyaa J. Jasim, Arsalan Khadim Mahmood

“…The study utilizes an improved arithmetic optimization algorithm (IAOA) to optimize component sizes and MRUs, incorporating a neighborhood search operator to enhance performance and prevent premature convergence. …”
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Coal Price Forecasting Using CEEMDAN Decomposition and IFOA-Optimized LSTM Model by Zhuang Liu, Xiaotuan Li

“…Abstract This study introduces a novel hybrid forecasting model for coking coal prices, integrating complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and long short-term memory (LSTM) neural networks, enhanced by an improved fruit fly optimization algorithm (IFOA). The approach begins with CEEMDAN decomposing the coking coal price sequence into intrinsic mode functions (IMFs) and a residual component, effectively mitigating non-stationarity and nonlinearity. …”
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Optimal sizing and placement of STATCOM, TCSC and UPFC using a novel hybrid genetic algorithm-improved particle swarm optimization by Urbanus Mwanzia Ngei, Abraham Mutunga Nyete, Peter Musau Moses, Cyrus Wekesa

“…A novel Genetic Algorithm-Improved Particle Swarm Optimization (GA-IPSO) technique is proposed in this paper for optimization of size and location of FACTS devices. …”
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Multimodal Transport Path Selection of Cold Chain Logistics Based on Improved Particle Swarm Optimization Algorithm by Changjiang Zheng, Kai Sun, Yuhang Gu, Jinxing Shen, Muqing Du

“…An improved particle swarm optimization algorithm (IPSO) is introduced to address the model and is proven to retain a fast convergence rate and achieve outstanding solving accuracy through the experimental study. …”
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Research on Optimal Configuration of Offshore Wind Power Energy Storage Based on Improved Scene Clustering Algorithm by Jingui YI, Ziwei ZHU, Qing XIE

“…Furthermore, to minimize the annual comprehensive cost of the power storage, the paper constructs an optimal configuration model for offshore wind power storage and uses the particle swarm optimization algorithm to solve the optimal configuration model. …”
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Data-driven continuous-time Hammerstein modeling with missing data using improved Archimedes optimization algorithm by Muhammad Shafiqul Islam, Mohd Ashraf Ahmad

“…This research introduces the improved Archimedes optimization algorithm (IAOA) for data-driven modeling of continuous-time Hammerstein models with missing data. …”
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Feature selection using a multi-strategy improved parrot optimization algorithm in software defect prediction by Qi Fei, Guisheng Yin, Zhian Sun

“…The proposed approaches in this study hold significant practical value, particularly in improving software quality, optimizing testing resource allocation, and reducing maintenance costs, offering broad potential for application in real-world software engineering scenarios.…”
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Improving kernel ridge regression for medical data classification based on meta-heuristic algorithms

“…The development of meta-heuristic algorithms has helped in solving difficult issues. In this paper, the main improvement is included in the pelican optimization algorithm by applying elite opposite-based learning (EOBL) to improve population diversity in the search space for selecting the best hyperparameters. …”
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Research on site selection and capacity determination problem based on improved particle swarm algorithm by Xiaotong Mi, Qinyang Liu, Bo Geng, Yong Zhu

“…Abstract To promote the effective utilization of distributed power sources after grid connection and achieve the goal of maximizing energy transmission efficiency and minimizing cost, this paper proposes a scheme based on the integration of the improved particle swarm optimization algorithm and the improved ant colony optimization algorithm (IPSOACO). …”
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An improvement in the design process of sustainable peak power rating transformer for solar utility by Emir Yükselen, Ebrahim Rahimpour

“…Such upgrades are essential for transitioning to a zero-emission electricity system and developing green energy projects.In this paper, a transformer has been studied using a combination of electrical design and 3D finite element method simulation to evaluate various design parameters. An optimization study has been conducted using an innovative multi-objective genetic algorithm utilizing a cost function that factors in size and material costs to identify the most efficient and cost-effective design solutions.The proposed design method was then validated through thermal model simulations and experimental tests based on the photovoltaic load cycle. …”
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Shuffled Puma Optimizer for Parameter Extraction and Sensitivity Analysis in Photovoltaic Models by En-Jui Liu, Rou-Wen Chen, Qing-An Wang, Wan-Ling Lu

“…To address this challenge, a novel metaheuristic algorithm called shuffled puma optimizer (SPO) is deployed to perform parameter extraction and optimal configuration identification across four PV models. …”
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Improved Quantum Artificial Bee Colony Algorithm-Optimized Artificial Intelligence Models for Suspended Sediment Load Predicting by Peng Wei, Wang Yu

“…To evaluate the predictive capability, the models are compared with quantum bee colony algorithm-optimized AI models (QABC-SVR and QABC-ANN), genetic algorithm-optimized AI models (GA-SVR and GA-ANN) and traditional AI models (SVR and ANN). …”
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