Search Results - (( location selection models algorithm ) OR ( based optimization means algorithms ))*
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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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The performance of Taguchi�s T-method with binary bat algorithm based on great value priority binarization for prediction
Published 2023“…This paper proposes an optimization algorithm based on the Binary Bat algorithm methodology for replacing the conventional orthogonal array approach. …”
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Development of integrated models for distribution network design of perishable products
Published 2015“…A Lagrangian relaxationbased heuristic algorithm is developed to solve the model. The algorithm produces solutions that are within 0.027% of optimality gap.…”
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Crossover and mutation operators of real coded genetic algorithms for global optimization problems
Published 2016“…On another note, the drawback in CS is in locating the most stable conformation of a molecule with the minimum potential energy based on a mathematical function. …”
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Assessment of suitable hospital location using GIS and machine learning
Published 2022“…First, the conditioning factors were optimized and ranked to identify and select the most correlated factors to predict the suitability of a hospital site by applying the correlation feature selection (CFS) algorithm and the greedy-stepwise search method. …”
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7
Impact of BPL penalty functions and PSF models in PET/CT radial spatial resolution recovery
Published 2024“…Advanced reconstruction algorithms like TOF, BPL, and PSF models, along with OSEM have shown spatial resolution enhancements based on the FWHM measured. …”
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Big Data in Motion: A Vehicle-Assisted Urban Computing Framework for Smart Cities
Published 2019“…The proposed framework can also facilitate the research community to benchmark their own route selection algorithms easily. Further, we performed an extensive evaluation of the proposed framework based on realistic models of vehicles, routes, data-spots, data chunks to be transmitted and the energy consumed. …”
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Pid-aco vibration controller with magnetorheological damper for wind turbine tower / Mahmudur Rahman
Published 2019“…It is found that wind turbine tower vibration is reduced up 72% when the damper is placed at middle of the tower and the selection of this optimal location is also based on considerations such as design complexity and maintenance cost. …”
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Channel Modeling and Direction-of-Arrival Estimation in Mobile Multiple-Antenna Communication Systems
Published 2005“…The model can be applied to evaluate smart antenna systems and beamforming algorithms in the uplink by generating uncorrelated multipaths Rayleigh fading waveforms with certain spatio-temporal correlation and spatial coordinates relative to base stations to simulate received signals from mobiles and interferers. …”
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11
Reservoir Inflow Forecasting Using Artificial Neural Network and Adaptive Neuro-Fuzzy Inference System Techniques
Published 2007“…The model was trained based on the Leven-berg Marquardt algorithm with sigmoid activation functions. …”
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Optimal neural network approach for estimating state of energy of lithium-ion battery using heuristic optimization techniques
Published 2023Conference Paper -
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Optimized clustering with modified K-means algorithm
Published 2021“…Among the techniques, the k-means algorithm is the most commonly used technique for determining optimal number of clusters (k). …”
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Impact of evolutionary algorithm on optimization of nonconventional machining process parameters
Published 2025“…This paper presents the optimization of laser beam machining in additive manufacturing of polymer-based material parameters, specifically focusing on cutting speed, gas pressure of nitrogen, and focal point locations, to achieve optimal mean surface roughness. …”
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Document clustering based on firefly algorithm
Published 2015“…Document clustering is widely used in Information Retrieval however, existing clustering techniques suffer from local optima problem in determining the k number of clusters.Various efforts have been put to address such drawback and this includes the utilization of swarm-based algorithms such as particle swarm optimization and Ant Colony Optimization.This study explores the adaptation of another swarm algorithm which is the Firefly Algorithm (FA) in text clustering.We present two variants of FA; Weight- based Firefly Algorithm (WFA) and Weight-based Firefly Algorithm II (WFAII).The difference between the two algorithms is that the WFAII, includes a more restricted condition in determining members of a cluster.The proposed FA methods are later evaluated using the 20Newsgroups dataset.Experimental results on the quality of clustering between the two FA variants are presented and are later compared against the one produced by particle swarm optimization, K-means and the hybrid of FA and -K-means. …”
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Fuzzy C-Mean And Genetic Algorithms Based Scheduling For Independent Jobs In Computational Grid
Published 2006“…Our model presents the method of the jobs classifications based mainly on Fuzzy C-Mean algorithm and mapping the jobs to the appropriate resources based mainly on Genetic algorithm. …”
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Modified archive update mechanism of multi-objective particle swarm optimization in fuzzy classification and clustering
Published 2022“…Among multi-objective evolutionary algorithms proposed in the literature, particle swarm optimization (PSO)-based multi-objective (MOPSO) algorithm has been cited to be the most representative. …”
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Cluster optimization in VANET using MFO algorithm and K-Means clustering
Published 2023“…Proven to be an effective and efficient method for solving optimization problem. To design K-Means algorithm that portion nodes based on their proximities by optimize the distance between nodes within same cluster by assigning them to the closet cluster center. …”
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Efficient genetic partitioning-around-medoid algorithm for clustering
Published 2019“…Adopting the medoid instead of the mean can enhance the efficiency. However, the complexity of the kmedoid based algorithms in general is more than the complexity of the k-means based algorithms. …”
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