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421
Predicting excavation-induced lateral displacement using improved particle swarm optimization and extreme learning machine with sparse measurements
Published 2025-08-01“…This study presents a novel prediction method using an extreme learning machine (ELM) optimized by an improved particle swarm optimization (IPSO) algorithm. …”
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422
THE ALGORITHMIC MODEL OF LABORATORY DIAGNOSTICS OPTIMIZATION
Published 2015-12-01“…Introduction of algorithmic approach is able to optimize diagnostics and its costs. …”
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423
Optimal Configuration of Electricity-Hydrogen Hybrid Energy Storage System Based on Multi-objective Artificial Hummingbird Algorithm
Published 2023-07-01“…The multi-objective artificial hummingbird algorithm based on Pareto is used to solve the planning scheme and then compared with the multi-objective particle swarm optimization and multi-objective atomic orbital search algorithm. …”
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424
An Improved NSGA‐III With Hybrid Crossover Operator for Multi‐Objective Optimization of Complex Combined Cooling, Heating, and Power Systems
Published 2025-04-01“…The effectiveness of CCHP‐Plus is assessed using three key indicators: primary energy consumption, operational cost, and CO2 emissions. NSGAIII‐AC‐GM delivers a 20% reduction in operational costs and a 10% decrease in CO2 emissions, outperforming seven other algorithms in optimization efficiency on DTLZ and IMOP problems. …”
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425
Revolutionizing Electric Vehicle Charging Stations with Efficient Deep Q Networks Powered by Multimodal Bioinspired Analysis for Improved Performance
Published 2025-03-01“…These approaches rely on fixed models, often leading to inefficient energy use, higher operational costs, and increased traffic congestion. This paper proposes a novel framework that integrates deep Q networks (DQNs) for real-time charging optimization, coupled with multimodal bioinspired algorithms like ant lion optimization (ALO) and moth flame optimization (MFO). …”
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426
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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427
Assessment of energy management and power quality improvement of hydrogen based microgrid system through novel PSO-MWWO technique
Published 2025-01-01“…The achieved results and numerical analysis affirm the superiority of the proposed technique compared to other traditional methods like mixed integer linear programming (MILP), HOMER, Variable mesh optimization (VMO), and Cataclysmic genetic algorithm in optimizing component sizing, renewable production, hydrogen production, reliability, cost effective, and overall efficacy. …”
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428
A Theoretical Bound Which Improves the Performance of Compilation-Based Multi-Agent Path Finding
Published 2025-01-01Get full text
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429
Multi-Target Firefighting Task Planning Strategy for Multiple UAVs Under Dynamic Forest Fire Environment
Published 2025-02-01“…Results from benchmark tests and case studies indicate that the improved MP–GWO algorithm outperforms the grey wolf optimizer (GWO), pelican optimizer (POA), Harris hawks optimizer (HHO), coyote optimizer (CPO), and particle swarm optimizer (PSO) in solving more complex optimization problems, providing better average results, greater stability, and effectively reducing flight time and path cost. …”
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430
Optimizing FACTS Device Placement Using the Fata Morgana Algorithm: A Cost and Power Loss Minimization Approach in Uncertain Load Scenario-Based Systems
Published 2025-01-01“…The FATA algorithm is evaluated against recently developed and improved optimization techniques, such as rime-ice formation phenomenon based Improved RIME (IRIME) Algorithm, Newton–Raphson-Based Optimization (NRBO), Resistance Capacitance Algorithm (RCA), Krill Optimization Algorithm (KOA), and Grey Wolf Optimizer (GWO), across multiple optimization objectives: reduction in generation cost, reduction in power loss and combined generation cost plus power loss, termed as Gross cost function. …”
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431
Research on manufacturing quality improvement based on product gene evaluation method and a meta-heuristic algorithm with hybrid encoding scheme
Published 2025-07-01“…To address the model, an improved genetic algorithm (GA) and artificial bee colony algorithm (ABC) with hybrid encoding scheme (H-IGA-IABC) is designed by considering the different types of gene elements. …”
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432
Prediction of Spatiotemporal Distribution of Electric Vehicle Charging Load Based on Multi-Source Information
Published 2025-06-01“…Additionally, the Dijkstra algorithm is improved to plan charging paths more effectively by including real-time road condition data. …”
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433
Low Carbon Economic Dispatch of Power System Based on Multi-Region Distributed Multi-Gradient Whale Optimization Algorithm
Published 2025-08-01“…In this study, MRDMGWOA is simulated on the IEEE 39 system and 118 system, and its performance is compared with other heuristic algorithms. The results show that: (1) in the IEEE 39 system, MRDMGWOA reduces the power generation cost and CO<sub>2</sub> emission by 17% and 22%, respectively, and reduces the computation time by 16.14 s compared with the centralized optimization; (2) in the IEEE 118 system, the two metrics are further optimized, with a 20% and 17% reduction in the cost and emission, respectively, and an improvement in the computational efficiency by 45.46 s; (3) in the spacing, hypervolume, and Euclidian metrics evaluation, MRDMGWOA outperforms other algorithms; (4) compared with the existing DMOGWO and DMOMFO, the computation time of MRDMGWOA is reduced by 177.49 s and 124.15 s, respectively, and the scheduling scheme obtained by MRDMGWOA is more optimal than DMOGWO and DMOMFO.…”
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434
An effectiveness of machine learning models for estimate the financial cost of assistive services to disability care in the Kingdom of Saudi Arabia
Published 2025-03-01“…Eventually, the modified pelican optimization algorithm (MPOA) is utilized to fine-tune the optimal hyperparameter of ensemble model parameters to achieve high predictive performance. …”
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435
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436
TOPSIS inspired cost-efficient concurrent workflow scheduling algorithm in cloud
Published 2022-06-01“…Therefore, it is a great challenge to improve system performance and optimize several scheduling criteria simultaneously. …”
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437
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Optimization of integrated energy system considering P2G oxygen-enriched improvement and hybrid solar energy utilization
Published 2025-07-01“…Secondly, because the boiler efficiency is affected by the oxygen concentration, the optimal oxygen supply state for each period of the oxygen-consuming equipment is determined by a combined algorithm of genetic algorithm and Gurobi solver. …”
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439
Analysis of Sub-Synchronous Oscillation in Grid-Connected Wind Farm and Proposed Improved Solution
Published 2025-01-01“…Therefore, this paper proposes optimizing the internal control parameters of the RSC using meta-heuristic algorithms, including Particle Swarm Optimization (PSO), Cuckoo Search Algorithm (CSA), and Ant Colony Optimization (ACO). …”
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440
Towards Automated Cadastral Map Improvement: A Clustering Approach for Error Pattern Recognition
Published 2025-04-01Get full text
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