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Apllication of optimization algorithms to improve the design of turnouts
Published 2016-04-01“…One of the most important tasks for improving the infrastructure facility of railways is its optimization. …”
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Multiple R&D Projects Scheduling Optimization with Improved Particle Swarm Algorithm
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Designing a new optimal controller for a PEMFC by an improved design of the Coot Optimizer
Published 2025-05-01“…Comparative analyses against three other control techniques confirm a wide system enhancement, evidenced by a substantial reduction in both current and overshoot ripples. Algorithm verification using benchmark functions shows the ICOA achieves lower mean values and standard deviations, with p-values indicating statistically significant improvements (p < 0.05) in Root Mean Square Error (RMSE) compared to COA, MVO, EPO, and LOA algorithms, validating its enhanced optimization capabilities for PEMFC control.…”
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Design of efficient generalized digital fractional order differentiators using an improved whale optimization algorithm
Published 2025-07-01“…The proposed method utilizes an improved whale optimization algorithm (IWOA) to compute the optimal coefficients of IIR subfilters of the realization structure. …”
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Congestion Management Using an Optimized Deep Convolution Neural Network in Deregulated Environment
Published 2023-08-01“…This analysis incorporates restrictions such as line loads, bus voltage influence, generator, line limits, etc. The most important results for the test system indicating convergence profile, congestion cost, and change in real-power and voltage magnitude are obtained by the simulation in MATLAB, and on the basis of the obtained simulation outcomes, it is evident that the proposed Improved Lion Algorithm optimized Deep Convolution Neural Network displays phenomenal computation performance in minimizing congestion losses at minimum congestion costs. …”
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Research on Robot Path Planning Based on Improved RRT-Connect Algorithm
Published 2025-02-01“…Firstly, an improved RRT algorithm is employed to search and add a middle root node, facilitating the simultaneous expansion of four random trees to expedite algorithm convergence. …”
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An improved Multi-Objective Whale Optimization Algorithm for hydrodynamic and acoustic performance optimization of Myring-shaped underwater vehicle
Published 2025-12-01“…These improvements enhance the algorithm’s capability in solving Multi-Objective Optimization (MOP) problems. …”
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Improved Monarch Butterfly Optimization Algorithm Based on Opposition-Based Learning and Random Local Perturbation
Published 2019-01-01“…Many optimization problems have become increasingly complex, which promotes researches on the improvement of different optimization algorithms. …”
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Enhanced Dung Beetle Optimizer-Optimized KELM for Pile Bearing Capacity Prediction
Published 2025-07-01“…In response to the need for rapid and precise predictions of pile bearing capacity, this study introduces a kernel extreme learning machine (KELM) prediction model optimized through a multi-strategy improved beetle optimization algorithm (IDBO), referred to as the IDBO-KELM model. …”
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Structural Simulation Model Updating Based on Improved MCMC Algorithm and Surrogate Model
Published 2025-08-01“…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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Coal Price Forecasting Using CEEMDAN Decomposition and IFOA-Optimized LSTM Model
Published 2025-07-01“…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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An Adaptive Fusion Path Tracking Strategy for Autonomous Vehicles Based on Improved ACO Algorithm
Published 2025-01-01“…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
Published 2025-06-01Get full text
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Shuffled Puma Optimizer for Parameter Extraction and Sensitivity Analysis in Photovoltaic Models
Published 2025-07-01“…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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An improvement in the design process of sustainable peak power rating transformer for solar utility
Published 2025-09-01“…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
Published 2025-01-01“…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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Prediction of Earthquake Death Toll Based on Principal Component Analysis, Improved Whale Optimization Algorithm, and Extreme Gradient Boosting
Published 2025-08-01“…Accurate prediction of earthquake fatalities is of great importance for pre-disaster prevention and mitigation planning, as well as post-disaster emergency response deployment. 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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