Search Results - (( data optimization max algorithm ) OR ( parallel simulation modified algorithm ))
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1
Parallel algorithms for numerical simulations of EHD ion-drag micropump on distributed parallel computing systems
Published 2014“…The results showed that the parallel algorithms for EHD simulations may provide 4 to 5 times more speedup over sequential algorithm for large grid sizes. …”
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2
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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3
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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4
Maximum 2-satisfiability in radial basis function neural network
Published 2020“…In this study, the effectiveness of RBFNN-MAX2SAT can be estimated by evaluating the proposed models with testing data sets. …”
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5
A New Technique To Design Coating Structure For Energy Saving Glass Using The Genetic Algorithm
Published 2017“…After modifying these shapes using the Genetic algorithm and Parallel Genetic algorithm, the outputs are simulated in the Computer Simulation Technology (CST) simulation software. …”
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6
A modified artificial neural network (ANN) algorithm to control shunt active power filter (SAPF) for current harmonics reduction
Published 2013“…The novelty control design is an artificial neural network (ANN) adopting a modified mathematical algorithm (a modified delta rule weight-updating W-H) and a suitable alpha value (learning rate value) which determines the filters optimal operation. …”
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7
A Comparative Study of Z-Score and Min-Max Normalization for Rainfall Classification in Pekanbaru
Published 2024“…Data preprocessing plays a crucial role in enhancing the performance of machine learning algorithms for classification tasks. …”
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Prediction and multi-criteria-based schemes for seamless handover mechanism in mobile WiMAX networks
Published 2013“…Mobile WiMAX introduces several interesting advantages including last mile wireless access, variable and high data rate, point to multi-point communication, large frequency range and QoS (Quality of Service) for various types of applications. …”
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9
Energy-efficient base station transmission design for green 5G massive MIMO and hybrid networks
Published 2021“…The proposed algorithm maximizes the EE by jointly optimizing the minimum data rate requirement, the number of BS antennas and users. …”
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10
Improvement of Centralized Routing and Scheduling Using Cross-Layer Design and Multi-Slot Assignment in Wimax Mesh Networks
Published 2009“…This thesis proposes an optimized strategy namely cross-layer design in routing algorithms used find the best route for all SSs and scheduling algorithms, used to assign a time slot for each possible node transmission. …”
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11
Data normalization techniques in swarm-based forecasting models for energy commodity spot price
Published 2014“…Data mining is a fundamental technique in identifying patterns from large data sets.The extracted facts and patterns contribute in various domains such as marketing, forecasting, and medical.Prior to that, data are consolidated so that the resulting mining process may be more efficient.This study investigates the effect of different data normalization techniques.which are Min-max, Z-score and decimal scaling, on Swarm-based forecasting models.Recent swarm intelligence algorithms employed includes the Grey Wolf Optimizer (GWO) and Artificial Bee Colony (ABC).Forecasting models are later developed to predict the daily spot price of crude oil and gasoline.Results showed that GWO works better with Z-score normalization technique while ABC produces better accuracy with the Min-Max.Nevertheless, the GWO is more superior than ABC as its model generates the highest accuracy for both crude oil and gasoline price.Such a result indicates that GWO is a promising competitor in the family of swarm intelligence algorithms.…”
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Development of optimization Alghorithm for uncertain non-linear dynamical system
Published 2004“…The first is the use of momentum terms and the second is the parallel tangent method. Two new algorithms named DISOPE-MOMENTUM and DISOPE-PARTAN sprouted from these modifications and extensive simulations were performed to observe their performances. …”
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Monograph -
14
Statistical data preprocessing methods in distance functions to enhance k-means clustering algorithm
Published 2018“…The suggested approaches are called new approach to min-max (NAMM) and decimal scaling (NADS). The Hybrid mean algorithms which are based on spherical clusters is also proposed to remedy the most significant limitation of the K-Means and K-Midranges algorithms. …”
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15
Adaptive resource allocation algorithms with QoS support in OFDMA-based WiMAX networks
Published 2014“…In Worldwide Interoperability for Microwave Access (WiMAX) the primary concern is Quality of Service (QoS) support which aims to satisfy the diverse service requirements and to guarantee higher data rates allocation for different service classes. …”
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Electric vehicle battery state of charge estimation using metaheuristic-optimized CatBoost algorithms
Published 2025“…Three distinct metaheuristic algorithms were investigated: Barnacles Mating Optimizer (BMO), Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Whale Optimization Algorithm (WOA), each integrated with CatBoost to optimize critical parameters including learning rate, tree depth, regularization, and bagging temperature. …”
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Process Planning Optimization In Reconfigurable Manufacturing Systems
Published 2008“…The five (5) AADTs include; a variant of the simulated annealing algorithm that implements heuristic knowledge at critical decision points, two (2) cooperative search schemes based on a “loose hybridization” of the Boltzmann Machine algorithm with (i) simulated annealing, and (ii) genetic algorithm search techniques, and two (2) modified genetic algorithms. …”
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18
Analysis of optimizers on AlexNet architecture for face biometric authentication system
Published 2022“…The experiment shows AdaMax performs well when compared to the other optimizers on the proposed dataset.…”
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Proceeding Paper -
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Peningkatan halaju suapan maksimum penginterpolasi CNC dedenyut rujukan menggunakan pengaturcaraan selari
Published 2011“…The main research objective is to modify the existing Wan Yusoff reference-pulse CNC interpolator and Omirou reference-pulse CNC interpolator using parallel programming to increase maximum allowable feed rate. …”
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20
Artificial neural network-salp-swarm algorithm for stock price prediction
Published 2024“…The results show that the SSA-ANN model outperforms other models when applied to normalized data. Additionally, the SSA-ANN model is compared with other two hybrid models: the ANN optimized by the Whale Optimization Algorithm (WOA-ANN) and Moth-Flame Optimizer (MOA-ANN), as well as a single model, namely the Autoregressive Integrated Moving Average (ARIMA). …”
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