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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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343
Assimilating Satellite-Based Biophysical Variables Data into AquaCrop Model for Silage Maize Yield Estimation Using Water Cycle Algorithm
Published 2024-12-01“…Based on our proposed workflow in previous studies, a Gaussian process regression–particle swarm optimization (GPR-PSO) algorithm and global sensitivity analysis were applied to retrieve the fCover and biomass from Sentinel-2 satellite data and to identify the most sensitive parameters in the AquaCrop model, respectively. …”
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344
Artificial Flora Algorithm-Based Feature Selection With Support Vector Machine for Cardiovascular Disease Classification
Published 2025-01-01“…This approach utilizes the Cleveland dataset by combining the Artificial Flora Optimization algorithm with the Support Vector Machine. …”
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345
A Deep Reinforcement Learning-Driven Seagull Optimization Algorithm for Solving Multi-UAV Task Allocation Problem in Plateau Ecological Restoration
Published 2025-06-01“…The algorithm improves both global and local search capabilities by optimizing key phases of seagull migration, attack, and post-attack refinement. …”
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346
Identifying optimized spectral and spatial features of UAV-based RGB and multispectral images to improve potato nitrogen content estimation
Published 2025-12-01“…Based on the evaluation of RReliefF algorithm, the RGB-based multi-scale texture and MS-based spectral indices were the most important for PNC. …”
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347
Bus frequency optimization in a large-scale multi-modal transportation system: integrating 3D-MFD and dynamic traffic assignment
Published 2023-12-01“…However, as far as the authors know, most proposed bus frequency optimization formulations are based on static demand and the Bureau of Public Roads function, and do not properly consider the congestion dynamics and their impacts on mode choices. …”
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348
Arithmetic coder optimization for compressing images obtained through remote probing of water bodies
Published 2019-04-01“…In the course of work, the most computationally complex parts of the arithmetic coder algorithm are determined. …”
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349
Research on Oil Well Production Prediction Based on GRU-KAN Model Optimized by PSO
Published 2024-11-01“…First, the MissForest algorithm is employed to handle anomalous data, improving data quality. …”
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350
Research on Lithium-Ion Battery State of Health Prediction Based on XGBoost–ARIMA Joint Optimization
Published 2025-05-01Get full text
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351
Application of harmony search algorithm in optimizing autoregressive integrated moving average: A study on a data set of Coronavirus Disease 2019
Published 2024-12-01“…In this paper, a music-inspired metaheuristic optimization algorithm, named Harmony Search (HS), has been integrated with ARIMA in order to improve the forecasting of the COVID-19 data set. …”
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352
Enhanced OCR Recognition for Madurese Text Documents: A Genetic Algorithm Approach with Tesseract 5.5
Published 2025-08-01“…Character Recognition (OCR) for the Madurese language using Genetic Algorithms (GA). The study addresses the challenges in processing Madurese text documents by implementing a nine-step image preprocessing workflow optimized through GA. …”
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353
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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354
A two stage differential evolution algorithm for parameter estimation of proton exchange membrane fuel cell
Published 2025-02-01“…Abstract Precise models predicting fuel cell performance under different operating conditions require accurate parameter identification in a proton exchange membrane fuel cell (PEMFC). Most traditional parameter estimation methodologies depend on optimization algorithms which are limited in their efficiency, convergence speed, and robustness. …”
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Transfer Learning based Image Classification of Diseased Tomato Leaves with Optimal Fine-Tuning combined with Heat Map Visualization
Published 2023-11-01“…It is presumed that the implementation of deep learning algorithms demands a large amount of data to learn complex features automatically and this can pose a challenge for applications with lesser data to achieve generalization. …”
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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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Implementing an Industry 4.0 UWB-Based Real-Time Locating System for Optimized Tracking
Published 2025-03-01Get full text
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360
A genetic algorithm-based solution for multi-type maximal covering location problem (MMCLP): application to defense and deterrence
Published 2024-12-01“…Design/methodology/approach – In our case study, we use open source geographic and demographic data from Canadian sources as inputs to our optimization problem. Due to the complexity of the MIP formulation, we propose a hybrid metaheuristic solution approach, for which a genetic algorithm (GA) is proposed and integrated with local and large neighborhood search operators. …”
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