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Adaptive crayfish optimization algorithm for multi-objective scheduling optimization in distributed production workshops
Published 2025-06-01“…Furthermore, an improved crowding distance calculation enhances the algorithm’s performance in multi-objective optimization by improving solution distribution. …”
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202
Illustration Design Model with Clustering Optimization Genetic Algorithm
Published 2021-01-01“…This paper proposes an illustration art design model based on operator and clustering optimization genetic algorithm. First, during the operation of the genetic algorithm, the values of the crossover probability and the mutation probability are dynamically adjusted according to the characteristics of the population to improve the search efficiency of the algorithm, then the k-medoids algorithm is introduced to optimize the clustering of the genetic algorithm, and a cost function is used to carry out and evaluate the quality of clustering to optimize the complexity of the original algorithm. …”
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203
Logarithmic mean optimization a metaheuristic algorithm for global and case specific energy optimization
Published 2025-05-01“…In a real-world application, LMO was employed to optimize a hybrid photovoltaic (PV) and wind energy system, achieving a 5000 kWh energy yield at a minimized cost of $20,000, outperforming all other algorithms in both efficiency and effectiveness. …”
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204
Improving the performance of a two-phase ejector using genetic algorithm based on secondary fluid entrainment rate
Published 2022-12-01“…Using a multi-objective genetic algorithm, the optimal values for each parameter are obtained. …”
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205
Variance Reduction Optimization Algorithm Based on Random Sampling
Published 2025-03-01“…The main feature of the algorithm including an inner and outer double loop structure is designed: the outer loop structure uses mini-batch random samples to calculate the gradient, approximating the full gradient and reducing the gradient calculation cost; the inner loop structure also uses mini-batch random samples to calculate the gradient and replace the single sample random gradient, improving convergence stability of the algorithm. …”
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206
Increasing integration of wind energy through the joint operation of electric vehicles and the grid using the intelligent spider monkey algorithm
Published 2025-04-01“…A significant innovation involves demonstrating that prohibitive constraints on simultaneous charging and discharging can, under specific conditions, be relaxed without compromising system stability, thereby simplifying the optimization process. The optimization problem is formulated as a single objective problem and solved using an improved spider monkey optimization algorithm. …”
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207
Optimization of the Weight Processing Algorithm in Multichannel Doppler Filtering
Published 2024-05-01“…Separate optimization of weighting processing for each frequency channel can significantly improve the average efficiency characteristics of a multichannel Doppler filter and eliminate all the shortcomings of the classical and modified FFT algorithms when processing non-equidistant pulse sequences. …”
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208
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Optimal Placement of Phasor Measurement Unit in Electrical Grid Using Dingo Optimization Algorithm
Published 2025-05-01“…The study utilizes the Dingo Optimization Algorithm, a metaheuristic inspired by nature, to identify the best PMU placement. …”
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210
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211
Comparative study of whale optimization algorithm and flower pollination algorithm to solve workers assignment problem
Published 2022-01-01“…The WAP is to find the best assignment of workers to training courses such that the total training cost is minimized. Two metaheuristic optimizations named Whale Optimization Algorithm (WOA) and Flower Pollination Algorithm (FPA) are utilized to final the optimal solution that reduces the total cost. …”
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212
Path Planning of Intelligent Mobile Robots with an Improved RRT Algorithm
Published 2025-03-01“…Addressing issues such as pronounced randomness, low search efficiency, inefficient utilization of effective points, suboptimal path smoothness, and potential deviations from the optimal path in the RRT algorithm based on random sampling, we proposed an optimization algorithm that integrates Kalman filtering to eliminate redundant points along the path. …”
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213
Multi-clustering algorithm based on improved tensor chain decomposition
Published 2025-06-01“…The innovations were mainly reflected in two aspects: firstly, a new tensor decomposition framework was proposed, which effectively reduced the storage cost and improved the computational efficiency by optimizing the objective function; secondly, the improved tensor decomposition technique was applied to three main multi-clustering algorithms, including self-weighted multi-view clustering (SwMC), latent multi-view subspace clustering (LMSC), and multi-view subspace clustering with intactness-aware similarity (MSC IAS), which significantly improved the accuracy and efficiency of clustering. …”
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214
Distributed Optimization Strategy for Voltage Regulation in PV-Integrated Power Systems with Limited Sensor Deployment
Published 2025-07-01“…The methodology integrates an adaptive step size algorithm within a dynamic projected primal–dual distributed optimization framework, eliminating manual parameter tuning requirements while ensuring theoretical convergence guarantees through Lyapunov stability analysis. …”
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215
An Improved SLIC Superpixel Segmentation Algorithm Combined with FPGA Technology
Published 2020-02-01“…In view of the large amount of calculations, complexity of algorithm and the implementation is slow The paper combines superpixel segmentation technology with FPGA parallel processing technology, and puts forward a method to realize the image segmentation algorithm on FPGA platform SLIC is a kind of fast image segmentation algorithm SLIC has a lot of improvements in efficiency, costing and segmentation results compared with traditional image segmentation algorithm On the basis of the principle of SLIC segmentation algorithm, we made a further improvement algorithm by optimizing the operation and extracting a small number of pixels of the original image to reduce computational complexity Finally, the last of the original image segmentation was achieved by K nearest neighbor classification process We completed the algorithm design on FPGA platform The simulation results show that the improved algorithm has a better segmentation results and the processing speed has about 40% promotion And the improved algorithm has a higher realtime performance…”
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216
Improving Trajectory Tracking of Differential Wheeled Mobile Robots With Enhanced GWO-Optimized Back-Stepping and FOPID Controllers
Published 2025-01-01“…Simulations demonstrate the superior performance of the proposed GWO-SMA algorithm compared to existing optimization techniques, such as Particle Swarm Optimization (PSO), Gazelle Optimization Algorithm (GOA), and its individual components, GWO and SMA, which have shown strong performance in recent literature for optimizing PID-type controllers. …”
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217
Improving aquifer vulnerability assessment and its explainability in the Zanjan aquifer: Integrating DRASTIC model and optimized long short-term memory-based metaheuristic algorith...
Published 2025-06-01“…The LSTM model was optimized using the particle swarm optimizer (PSO) and equilibrium optimizer (EO) metaheuristic algorithms. …”
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218
An optimal design method of the resonant-free C-type filter
Published 2024-11-01Get full text
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219
Improving frequency stability in grid-forming inverters with adaptive model predictive control and novel COA-jDE optimized reinforcement learning
Published 2025-05-01“…The offline phase employs a novel Hybrid Crayfish Optimization and Self-Adaptive Differential Evolution Algorithm (COA-jDE) to minimize the cost function $$U_{offline}$$ , deriving optimal control parameters (Q, R) before real-time deployment. …”
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220
ANFIS-optimized control for resilient and efficient supply chain performance in smart manufacturing
Published 2025-03-01“…This paper evaluates the supply chain (SC) using the adaptive neuro-fuzzy inference system (ANFIS) classification control algorithm to improve the SC performance, maximize the system quality, and minimize the cost. …”
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