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A Novel Exploration Stage Approach to Improve Crayfish Optimization Algorithm: Solution to Real-World Engineering Design Problems
Published 2025-06-01“…In order to compensate these shortcomings, this study proposes an Improved Crayfish Optimization Algorithm (ICOA) that designs the competition stage with three modifications: (1) adaptive step length mechanism inversely proportional to the number of iterations, which enables exploration in early iterations and exploitation in later stages, (2) vector mapping that increases stochastic behavior and improves efficiency in high-dimensional spaces, (3) removing the X<sub>shade</sub> parameter in order to abstain from early convergence. …”
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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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The Crossover strategy integrated Secretary Bird Optimization Algorithm and its application in engineering design problems
Published 2025-01-01“…An improved metaheuristic algorithm called the Crossover strategy integrated Secretary Bird Optimization Algorithm (CSBOA) is proposed in this work for solving real optimization problems. …”
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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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Chiller power consumption forecasting for commercial building based on hybrid convolution neural networks-long short-term memory model with barnacles mating optimizer
Published 2025-07-01“…Results demonstrate that the CNN-LSTM-BMO achieves superior performance with the lowest Root Mean Square Error (RMSE) of 0.5523 and highest R² value of 0.9435, showing statistically significant improvements over other optimization methods as confirmed by paired t-tests (P < 0.05). …”
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Site Selection Optimization Strategy for Independent Secondary Device Integrated Center Based on Improved Artificial Bee Colony Algorithm
Published 2021-09-01“…Firstly, the possible interval of the optimal solution is calculated with the improved artificial bee colony algorithm; and then the ISDIC site node that is most suitable for the center is obtained through precise calculations; and finally the practical engineering significance of the model and the superiority of the method are fully illustrated through analyzing the indexes of the optimal node.…”
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Improving the Control Strategy of the DVR Compensator Based on an Adaptive Notch Filter with an Optimized PD Controller Using the IGWO Algorithm
Published 2024-01-01“…This article presents a DVR control scheme optimized with improved grey wolf optimization (IGWO) that uses a proportional derivative (PD) controller and adaptive notch filter (ANF). …”
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Bearing Fault Diagnosis Based on Parameter Optimized VMD and ELM with Improved SSA
Published 2023-10-01“…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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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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Improved cancer detection through feature selection using the binary Al Biruni Earth radius algorithm
Published 2025-03-01Get full text
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Research on path planning for mine rescue UAV based on improved Artificial Jellyfish Search algorithm
Published 2025-06-01“…To improve the path search efficiency and path optimization of mine rescue UAVs in environments with narrow passages and dense, complex obstacles, a path planning method based on the improved Artificial Jellyfish Search (IJS) algorithm was proposed. …”
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CRASHWORTHINESS DESIGN AND OPTIMIZATION FOR COLLISION POST OF TRAIN
Published 2022-01-01“…In order to improve the crashworthiness of the collision post structure, the optimal cross-section configuration of the collision post was obtained based on the topology optimization method, and the impacting finite element model of the collision post was established in the explicit dynamics software Ls-Dyna. …”
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Comprehensive recognition algorithm of RS code based on fast code root trial
Published 2022-11-01“…In order to solve the problem of high computation and high missed alarm probability of RS (Reed-Solomon) codes for recognition, comprehensive recognition algorithm of RS codes based on fast code root trial was proposed.Firstly, the check relationship was solved in binary equivalently and fast code root trial was used to check parameters in sequence.Secondly, according to distribution characteristics of the combined code roots, m-level primitive polynomial field and error correction ability was associatively determined.Finally, the short codes and long codes were given different confidence weights and the determined parameters were comprehensively analyzed.The optimal parameter was selected and the generate polynomial was calculated.The proposed algorithm did not need prior information such as signal-to-noise ratio (SNR), and had good adaptability.The simulation results show that the proposed algorithm can effectively reduce the missed alarm probability under the condition of low complexity.Compared with the conventional hard decision algorithm, the performance of the proposed algorithm is improved, and the parameter recognition of RS codes can be completed quickly.…”
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A model adapted to predict blast vibration velocity at complex sites: An artificial neural network improved by the grasshopper optimization algorithm
Published 2025-06-01“…Through a comprehensive evaluation of the running time results, the root mean square error (RMSE), mean absolute error (MAE), and determination coefficient (R2), a new algorithm, the grasshopper optimization algorithm (GOA), which is suitable for optimizing an ANN to predict PPV, is obtained. …”
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Tuning Genetic Algorithm Parameters to Improve Convergence Time
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