Search Results - (( using optimization means algorithm ) OR ( using optimization max algorithm ))
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An improvement of stochastic gradient descent approach for mean-variance portfolio optimization problem
Published 2021“…Furthermore, the applicability of SGD, Adam, AdaMax, Nadam, AMSGrad, and AdamSE algorithms in solving the mean-variance portfolio optimization problem is validated.…”
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Statistical data preprocessing methods in distance functions to enhance k-means clustering algorithm
Published 2018“…We introduced two new approaches to normalization techniques to enhance the K-Means algorithms. This is to remedy the problem of using the existing Min-Max (MM) and Decimal Scaling (DS) techniques, which have overflow weakness. …”
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Maximum 2-satisfiability in radial basis function neural network
Published 2020“…This paper presents a new paradigm in using MAX2SAT by implementing in Radial Basis Function Neural Network (RBFNN). …”
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Prediction and multi-criteria-based schemes for seamless handover mechanism in mobile WiMAX networks
Published 2013“…Finally, the FuzSAHO decision algorithim is optimized for real-time application, by using a new handover criteria, namely queue length besides RSSI and MS velocity. …”
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5
Social spider optimisation algorithm for dimension reduction of electroencephalogram signals in human emotion recognition
Published 2018“…Due to some limitations of current heuristics and evolutionary algorithms, this paper proposed a new swarm based algorithm for feature selection method called Social Spider Optimization (SSO-FS). …”
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Digital beamforming implementation of switch-beam smart antenna system by using integrated digital signal processor and field-programmable gate array
Published 2008“…Also, for more antenna radiation pattern optimization, the sidelobe cancellation is performed base on the chebyshev algorithm. …”
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Performance comparison of GA and PSO based ANN training on medical dataset / Muhammad Amirul Danish Jamal
Published 2025“…Data preprocessing was carried out using min-max normalization, and an ANN architecture featuring 20 hidden neurons was created and optimized with MATLAB. …”
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Dynamic transmit antenna shuffling scheme for hybrid multiple-input multiple-output in layered architecture
Published 2010“…The computational complexity (total number of arithmetic operations) of proposed LC-QR algorithm is significantly lower than the conventional QR decomposition, zero-forcing (ZF) and minimum mean square error (MMSE) detection algorithm. …”
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9
A Comparative Study of Z-Score and Min-Max Normalization for Rainfall Classification in Pekanbaru
Published 2024“…The findings demonstrate that applying normalization techniques effectively enhances classification performance compared to using unnormalized data. Specifically, the optimal classification performance is achieved through Z-Score Normalization, yielding accuracy, sensitivity, and specificity rates of 74.59%, 82.48%, and 63.92%, respectively.…”
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Optimization of hydropower reservoir system using genetic algorithm for various climatic scenarios
Published 2015“…In order to increase the system efficiency and maximize the power generation, constructed operation models were optimized. To determine the optimum solution in each policy, real coded genetic algorithm is used as an optimization technique. …”
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A comparative performance analysis of computational intelligence techniques to solve the asymmetric travelling salesman problem
Published 2021“…The comparative algorithms in this study employ different techniques in their search for solutions to ATSP: the African Buffalo Optimization employs the modified Karp–Steele mechanism, Model-Induced Max-Min Ant Colony Optimization (MIMM-ACO) employs the path construction with patching technique, Cooperative Genetic Ant System uses natural selection and ordering; Randomized Insertion Algorithm uses the random insertion approach, and the Improved Extremal Optimization uses the grid search strategy. …”
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Reactive max-min ant system: An experimental analysis of the combination with K-OPT local searches
Published 2015“…The exploration versus exploitation dilemma rises in ACO search.Reactive max-min ant system algorithm is a recent proposition to automate the exploration and exploitation.It memorizes the search regions in terms of reactive heuristics to be harnessed after restart, which is to avoid the arbitrary exploration later.This paper examined the assumption that local heuristics are useless when combined with local search especially when it applied for combinatorial optimization problems with rugged fitness landscape.Results showed that coupling reactive heuristics with k-Opt local search algorithms produces higher quality solutions and more robust search than max-min ant system algorithm.Well-known combinatorial optimization problems are used in experiments, i.e. traveling salesman and quadratic assignment problems. …”
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Automated characterization of coronary artery disease, myocardial infarction, and congestive heart failure using contourlet and shearlet transforms of electrocardiogram signal
Published 2017“…Only significant features are selected using improved binary particle swarm optimization (IBPSO) feature selection method. …”
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An optimal tasks scheduling algorithm based on QoS in cloud computing network
Published 2017“…This study presents an optimal task scheduling algorithm by enhancing Max-Min and TS algorithm. …”
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A comparative evaluation of heuristic and metaheuristic job scheduling algorithms for optimized resource management in cloud environments
Published 2026“…The CloudSim simulator is applied to evaluate each algorithm using key performance metrics, including makespan, average flow time, and the number of cloudlets that fail to meet deadlines. …”
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Fair uplink bandwidth allocation and latency guarantee for mobile WiMAX using fuzzy adaptive deficit round robin
Published 2014“…In this paper, an efficient bandwidth allocation algorithm for the uplink traffic in mobile WiMAX is proposed. …”
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Cross-layer design using multi-channel system in WiMAX mesh networks
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A new minimum pheromone threshold strategy (MPTS) for max-min ant system
Published 2009“…Among others is the ant colony optimization (ACO) algorithm, which was inspired by the foraging behavior of ants. …”
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An exploration technique for the interacted multiple ant colonies optimization framework
Published 2024Conference Paper
