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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The Optimal Design of HVDC Transmission Lines for the Improvement of Reactive Power Distribution Using Genetic Algorithm by Ali Mohammadi

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Integrated optimization model for production and equipment dispatching in underground mines by LI Guo-qing, HOU Jie, HU Nai-lian

“…The best result of mining sequence and equipment dispatching was obtained by an improved genetic algorithm which searches the feasible solutions through primary-secondary two-step searching method. …”
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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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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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An improved multi-objective artificial physics optimization algorithm based on R2 indicator and its application by Bao Sun, Yihong Chang, Min Gao, Zhanlong Li, Jiankang Liu, Jinbin Wang

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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

“…Comparison of GA-IPSO technique with other algorithms such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Improved Grey Wolf Optimization (IGWO) and Differential Evolution Algorithm (DEA) showed that the proposed hybrid technique was superior and more efficient in solving the FACTS optimization problem.…”
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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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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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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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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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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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Bearing Fault Diagnosis Based on Parameter Optimized VMD and ELM with Improved SSA by Yang Sen, Wang Hengdi, Cui Yongcun, Li Chang, Tang Yuanchao

“…Secondly, the improved SSA optimizes the important parameters (decomposition number <italic>K</italic> and penalty factor <italic>α</italic>) of the VMD algorithm, and the fittness function adopts the minimum envelope entropy. …”
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Prediction of Earthquake Death Toll Based on Principal Component Analysis, Improved Whale Optimization Algorithm, and Extreme Gradient Boosting by Chenhui Wang, Xiaotao Zhang, Xiaoshan Wang, Guoping Chang

“…To address the challenges of small sample sizes, high dimensionality, and strong nonlinearity in earthquake fatality prediction, this paper proposes an integrated modeling approach (PCA-IWOA-XGBoost) combining Principal Component Analysis (PCA), the Improved Whale Optimization Algorithm (IWOA), and Extreme Gradient Boosting (XGBoost). …”
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Tuning Genetic Algorithm Parameters to Improve Convergence Time by Maria Angelova, Tania Pencheva

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Groundwater level prediction using an improved SVR model integrated with hybrid particle swarm optimization and firefly algorithm by Sandeep Samantaray, Abinash Sahoo, Falguni Baliarsingh

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Optimized parameter estimation of lithium-ion batteries using an improved cuckoo search algorithm under variable temperature profile by Tasadeek Hassan Dar, Satyavir Singh

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An improved multiclass classification of acute lymphocytic leukemia using enhanced glowworm swarm optimization by Saranya N, Kalamani M

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