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Comprehensive optimization of active and reactive power scheduling in smart microgrids by accounting for line transmission losses using genetic algorithm
Published 2025-06-01“…The grid-connected SMG consists of photovoltaic (PV) cells, BSS, and residential loads. A Genetic Algorithm (GA)-based method is proposed to optimize power management in three scenarios: (i) active power only (AOM), (ii) active and reactive power without line losses (ARM), and (iii) active and reactive power considering line losses (ARLM). …”
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143
Research on Rolling Bearing Fault Diagnosis Using Improved Majorization-Minimization-Based Total Variation and Empirical Wavelet Transform
Published 2020-01-01“…However, manually selecting parameters requires professional experience in a process that it is time-consuming and laborious, while the use of genetic algorithms is cumbersome. Therefore, an improved particle swarm algorithm (IPSO) is used to find the optimal solution of λ. …”
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144
Optimizing Vehicle Routing for Perishable Products with Time Window Constraints:
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Multi-objective programming method for ship weather routing based on fusion of A* and NSGA-II
Published 2025-06-01“…ResultsThe simulation results demonstrate that the proposed model and algorithm can obtain a uniformly distributed and diversified Pareto optimal route set. …”
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147
Evolutionary Cost Analysis and Computational Intelligence for Energy Efficiency in Internet of Things-Enabled Smart Cities: Multi-Sensor Data Fusion and Resilience to Link and Devi...
Published 2025-04-01“…Thorough simulations and comparative analysis reveal the protocol’s superior performance across key performance metrics, namely, network lifespan, energy consumption, throughput, and average delay. When compared to the most recent and relevant protocols, including the Particle Swarm Optimization-based energy-efficient clustering protocol (PSO-EEC), linearly decreasing inertia weight PSO (LDIWPSO), Optimized Fuzzy Clustering Algorithm (OFCA), and Novel PSO-based Protocol (NPSOP), our approach achieves very promising results. …”
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148
AquaFlowNet a machine learning based framework for real time wastewater flow management and optimization
Published 2025-05-01“…These limitations often lead to inefficiencies such as energy wastage, treatment delays, and overflow incidents, negatively impacting system performance and sustainability.AquaFlowNet leverages state-of-the-art machine learning algorithms to analyze real-time data from sensors, forecast flow variations, and optimize wastewater treatment processes. …”
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149
Improvement of Network Traffic Prediction in Beyond 5G Network using Sparse Decomposition and BiLSTM Neural Network
Published 2025-04-01“…Next, sparse feature extraction is performed using Discrete Wavelet Transform (DWT), and a sparse matrix is constructed. A Genetic Algorithm (GA) is used to optimize the sparse matrix, which effectively selects the most significant features for prediction. …”
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150
Developing a novel hybrid model based on GRU deep neural network and Whale optimization algorithm for precise forecasting of river’s streamflow
Published 2025-06-01“…In this study, a novel innovative deep neural network (DNN) structure by integrating a double Gated Recurrent Units (GRU) neural network model with a multiplication layer and meta-heuristic whale optimization algorithm (WOA) (i.e., hybrid 2GRU×–WOA model) is developed to improve the prediction accuracy and performance of mean monthly Chehel-Chai River’s streamflow (CCRSF m ) in Iran. …”
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151
Environmental risk assessment based on multiscale spatial recurrent neural network algorithm for IoT agriculture area
Published 2025-07-01“…The Exhaustive Traffic Information Rate (ETIR) method evaluates the marginal rate of each feature, and the AntLion Behavior Optimization (ALBO) algorithm selects the most significant features, reducing dimensionality. …”
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152
Distributed robust planning for new power system considering uncertainty and frequency security
Published 2025-08-01“…Firstly, establish a system frequency model that provides frequency support for a fast frequency response energy storage system, and propose an improved segmented linearization algorithm to transform the constructed frequency safety constraints. …”
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153
Enhancing Harmony Search Metaheuristic Algorithm for Coverage Efficiency, Test Suite Reduction, and Running Time in Combinatorial Interaction Testing
Published 2025-01-01“…Optimization has developed powerful algorithms for solving complex problems efficiently. …”
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154
Financial Market Evaluation Utilizing an Optimized Deep-Learning Model: A Case Study of the Nikkei 225
Published 2025-06-01“…The precision of the stock market forecasts can be improved using metaheuristic algorithms such as the Moth-flame optimizer, which will provide the best optimization of the hyperparameters for an LSTM model. …”
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Association Analysis of Benzo[<i>a</i>]pyrene Concentration Using an Association Rule Algorithm
Published 2025-05-01“…Herein, the factors influencing B(a)P concentration were elucidated by analyzing the monthly environmental data for Kyoto, Japan, from 2001 to 2021 using an improved association rule algorithm. Results revealed that B(a)P concentrations were 1.3–3 times higher in cold seasons than in warm seasons and SPM concentrations were lower in cold seasons. …”
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157
Optimization of the flow guiding fins configuration and tube arrangements in a shell and tube heat exchanger: coupling response surface methodology and CFD
Published 2025-08-01“…The simulation results of the two-phase flow of water-MWCNT nanofluid in the optimal arrangement of conducting fins show that the heat transfer is improved and the coefficient of performance is greater than 1.…”
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158
Advanced skin cancer prediction with medical image data using MobileNetV2 deep learning and optimized techniques
Published 2025-08-01“…These results underscore the potential of deep learning models, optimized with the memetic algorithm, to significantly improve skin cancer detection. …”
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159
Opposition-based learning techniques in metaheuristics: classification, comparison, and convergence analysis
Published 2025-07-01“…In recent years, opposition-based learning (OBL) has emerged as a powerful enhancement strategy in metaheuristic algorithms (MAs), gaining significant attention for its potential to accelerate convergence and improve solution quality. …”
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Optimizing performance and economic viability of combined energy systems: A novel energy hub framework
Published 2025-06-01“…To solve this complex optimization problem, the spider monkey optimization (SMO) algorithm is modified and applied. …”
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