Search Results - (( using optimization clustering algorithm ) OR ( parameter optimization system algorithm ))
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…The fitness function used is the correlation function in the SKF algorithm to optimize the cipher image produced using the Lorenz system. …”
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Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed
Published 2012“…Genetic algorithm (GA) was employed to adjust parameters of FES and optimize the system. …”
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3
Single and Multiple variables control using Tree Physiology Optimization
Published 2017“…This paper presents the tuning of single-input single-output (SISO), and multiple-input multiple-output (MIMO) control system using Tree Physiology Optimization (TPO). TPO is a metaheuristic optimization algorithm that has a clustered diversification search strategy inspired from plant shoots growth. …”
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Whale optimization algorithm based on tent chaotic map for feature selection in soft sensors
Published 2025“…One of the powerful optimization algorithms that is used for feature selection is the Whale Optimization Algorithm (WOA), which is a nature-inspired metaheuristic optimization algorithm that mimics the social behavior of humpback whales. …”
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Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach
Published 2022“…The most popular method to solve parameter estimation problem is using optimization algorithm that easily trap to local minima and poor in exploitation to find the good solutions. …”
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Transmission path optimization Based on Efficiency Communication System
Published 2022“…In this paper, routing attribute table that is maintained by the nodes, the density and relative distance of node distribution, is used to determine the clustering method. At the same time, the developed algorithm combines the relative position of the cluster and the base station to further improve the routing method of the sub-cluster head, Finally, the algorithm analyzes the influence of different parameters on the transmission path, and use the simulation experiments to evaluate the conclusions.…”
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Regionalization by fuzzy expert system based approach optimized by genetic algorithm.
Published 2013“…Genetic algorithm (GA) was employed to adjust parameters of FES and optimize the system. …”
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Optimization of ANFIS with GA and PSO estimating α ratio in driven piles
Published 2020“…The system was optimized by changing the number of clusters in the FIS and then the output was used for the GA and PSO optimization algorithm. …”
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A new routing mechanism for energy-efficient in bluetooth mesh-low power nodes based on wireless sensor network
Published 2023“…Compared to the Ant Colony Optimization-Genetic Algorithm (ACO-GA) and Ant Colony Optimization- Hierarchical Clustering Mechanism (ACOHCM), the ACO algorithm shows superior power savings and efficiency. …”
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Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things
Published 2022“…The system trains the NN on previously labelled data, and its knowledge is used to calculate the core online-offline clustering block error. …”
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Activity recognition using optimized reduced kernel extreme learning machine (OPT-RKELM) / Yang Dong Rui
Published 2019“…ReliefF can solve the problem of large feature dimension in the existing RKELM. By using clustering method K-Means, we have found the best center point position to calculate Kernel matrix. at last, we have employed Quantum-behaved Particle Swarm Optimization (QPSO) to get the optimal kernel parameter in the proposed model. …”
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Taylor-Bird Swarm Optimization-Based Deep Belief Network For Medical Data Classification
Published 2022“…However, finding the most appropriate deep learning algorithm for a medical classification problem along with its optimal parameters becomes a difficult task. …”
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Green anaconda optimization based energy aware clustering protocol for 6G wireless communication systems
Published 2023“…In recent times, some considerations like high reliability and less energy consumption are essential to choosing the optimum CH nodes in clustering-related metaheuristic mechanisms. The selection of proper CHs using metaheuristic algorithms fnds useful in design of energy-efcient WSNs. …”
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Cauchy density-based algorithm for VANETs clustering in 3D road environments
Published 2022“…Clustering algorithms for VANETs operate in a decentralized mode, which requires incorporating additional stages before deciding the clustering decisions and might create sub-optimality due to the local nature of the decentralized approach. …”
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Development of compound clustering techniques using hybrid soft-computing algorithms
Published 2006“…The hierarchical fuzzy clustering algorithm developed in this work assign the overlapping structures (structures having more than one activity) to more than one clusters if their fuzzy membership values are significantly high for those clusters. …”
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Independent And Dependent Job Scheduling Algorithms Based On Weighting Model For Grid Environment
Published 2018“…As a result, researchers have tried to improve job scheduling system using multiple algorithms. However, the previous algorithms are complicated and needed a lot of computational resources. …”
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Adaptive manet OLSR routing protocol for optimal route selection in high dynamic network
Published 2020“…To provide the necessary robustness, a new Cluster-based Adoptive Cooperative Algorithm (CACA) for VANET is introduced to improve the scalability of the network and reduce control overhead. …”
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19
Case study : an effect of noise in character recognition system using neural network
Published 2003“…Neural networks are useful tools for solving many type of problems. These problems may be characterized as mapping(including pattern association and pattern classification), clustering and constrained optimization. …”
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Adaptive Neuro-Fuzzy Inference System for diagnosis risk in dengue patients
Published 2012“…The first model was developed by systematically optimizing the initial ANFIS model parameters while the second model was developed by employing the subtractive clustering algorithm to optimize the initial ANFIS model parameters. …”
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