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201
Forecasting Influenza Trends Using Decomposition Technique and LightGBM Optimized by Grey Wolf Optimizer Algorithm
Published 2024-12-01“…Accurate influenza prediction is a critical issue in public health and serves as an essential tool for epidemiological studies. This paper seeks to improve the prediction accuracy of influenza-like illness (ILI) proportions by proposing a novel predictive model that integrates a data decomposition technique with the Grey Wolf Optimizer (GWO) algorithm, aiming to overcome the limitations of current prediction methods. …”
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202
Comprehensive Study of Nonlinear Maglev System Utilizing COOT Optimized FOPID Controller
Published 2025-01-01“…To improve the performance of the magnetic levitation system, the most recent metaheuristic COOT algorithm was first employed in this study to tune the Fractional Order Proportional Integral and Derivative (FOPID) controller. …”
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203
Automated Calibration of SWMM for Improved Stormwater Model Development and Application
Published 2025-05-01“…The tool also supports parallelized optimization algorithms and utilizes Application Programming Interfaces (APIs) to dynamically update SWMM model parameters, accelerating both model execution and convergence. …”
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204
Identifying Capsule Defect Based on an Improved Convolutional Neural Network
Published 2020-01-01“…The improved CNN algorithm is based on regularization and the Adam optimizer (RACNN), on which a dropout layer and L2_regularization are added between the full connection and the output layer to solve the overfitting problem. …”
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205
RRMSE-enhanced weighted voting regressor for improved ensemble regression.
Published 2025-01-01“…This uniform weighting approach doesn't consider that some models may perform better than others on different datasets, leaving room for improvement in optimizing ensemble performance. To overcome this limitation, we propose the RRMSE (Relative Root Mean Square Error) Voting Regressor, a new ensemble regression technique that assigns weights to each base model based on their relative error rates. …”
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206
Local Outlier Detection Method Based on Improved K-means
Published 2024-07-01“…Hence, an improved K-means clustering algorithm is proposed by introducing fast search and discovering density peak methods. …”
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207
The Improved MNSPI Method for MODIS Surface Reflectance Data Small-Area Restoration
Published 2025-03-01Get full text
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208
Provide a method to diagnose and optimize diabetes using data mining methods and firefly algorithm
Published 2023-09-01“…In this research, the DBSCAN clustering algorithm is used to cluster the data. Then, using SVM, we classify the data to identify useful data, and finally, with the firefly algorithm, we increase the obtained data to increase we optimize performance with this algorithm. …”
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209
Intelligent Optimal Control of Sewage Treatment Based on Multiobjective Evolutionary Algorithm
Published 2022-01-01“…For each new solution generated by the MOEA/D algorithm, the improved algorithm in this paper finds the most suitable subproblem for the new solution from all subproblems and replaces the population in its neighborhood. …”
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210
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211
Control Optimization of Stochastic Systems Based on Adaptive Correction CKF Algorithm
Published 2020-01-01“…The control model is established by using the CKF algorithm, the covariance matrix of standard CKF is optimized by square root filter, the adaptive correction of error covariance matrix is realized by adding memory factor to the filter, and the disturbance factors in nonlinear time-varying discrete stochastic systems are eliminated by multistep feedback predictive control strategy, so as to improve the robustness of the algorithm. …”
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212
Maintenance and Operation Optimization Algorithm of PV Plants under Multiconstraint Conditions
Published 2020-01-01“…The proposed study is also applicable to multiple PV plants, multiple maintainers, multipoint departure, different dispatching conditions, and cost considerations. We propose an MOOA algorithm to solve this issue, and we strongly believe that, by defining a suitable fitness function, the convergence speed and optimization ability can be greatly improved, and this study puts a forward step.…”
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213
Predicting algorithm of attC site based on combination optimization strategy
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214
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215
Earthworm optimization algorithm for extracting parameters for solar cells and photovoltaic modules
Published 2025-08-01“…In this paper, we deal with the use of the earthworm optimization algorithm (EOA) in foraging to estimate and extract the intrinsic electrical parameters of single-, double-, and triple-diode solar cells and photovoltaic modules across different technologies. …”
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216
Gradient-Enhanced Kriging-Based Parallel Efficient Global Optimization Algorithm and Its Application in Aerodynamic Shape Optimization
Published 2025-01-01“…To further enhance the optimization potential of the parallel EGO algorithm, an improved system that integrates the parallel EGO algorithm with gradient-enhanced kriging (GEK) is proposed. …”
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217
GENETIC ALGORITHM IN OPTIMIZATION DESIGN OF INTERIOR PERMANENT MAGNET SYNCHRONOUS MOTOR
Published 2017-05-01“…For designing PMSM, evolution algorithms are more attractive approach. Genetic algorithm is one of the most common. …”
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218
Multi-objective optimization of a novel control algorithm and scheduling procedure for optimal use of energy storage systems
Published 2025-04-01“…Peak shaving with energy storage systems (ESSs) is a promising approach to optimize energy use, reduce costs, and ensure a more reliable power grid.This paper aims to improve the performance of a novel control algorithm for efficient peak shaving by using sensitivity analysis and multi-objective optimization techniques. …”
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219
Optimized Negative Selection Algorithm for Image Classification in Multimodal Biometric System
Published 2023-04-01“…Hence, this work developed an Optimized Negative Selection Algorithm (ONSA) for image classification in biometric systems. …”
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220
Optimized Intelligent Localization Through Mathematical Modeling and Crow Search Algorithms
Published 2025-08-01“…The modified CSA iteratively improves upon this estimate by emulating the natural behavior of crows, updating its variables to converge on the optimal position. …”
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