Search Results - (( using scale data algorithm ) OR ( based optimization based algorithm ))
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Optimization of RFID network planning for monitoring railway mechanical defects based on gradient-based Cuckoo search algorithm
Published 2020“…The Gradient-Based Cuckoo Search (GBCS) algorithm was used to achieve the final objective. …”
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Thesis -
2
Improved stochastic gradient descent algorithm with mean-gradient adaptive stepsize for solving large-scale optimization problems
Published 2023“…Stochastic gradient descent (SGD) is one of the most common algorithms used in solving large unconstrained optimization problems. …”
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Algorithm development for optimization of a refrigeration system
Published 2010“…The thesis describes the step by step the method to find an algorithm by using experimental data. Vapor compression refrigeration system was studied as it is the most widely used refrigeration system especially in small scale of refrigeration application such as in domestic application. …”
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Undergraduates Project Papers -
4
Voting algorithms for large scale fault-tolerant systems
Published 2011“…So far, various voting methods are proposed which are mostly proper for small-scale systems. In this research, we proposed optimal algorithms using Divide and Conquer, Brent’s theorem and parallel algorithms, appropriate for today’s large scale systems such as satellite processing systems, traffic control, weather forecasting which all face a large quantity of processing input data. …”
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5
Nonlinear identification of a small scale unmanned helicopter using optimized NARX network with multiobjective differential evolution
Published 2014“…This study proposes a hybrid of conventional back propagation training algorithm for the NARX network and multiobjective differential evolution (MODE) algorithm for identification of a nonlinear model of an unmanned small scale helicopter from experimental flight data.The proposed hybrid algorithm was able to produce models with Pareto-optimal compromise between the design objectives. …”
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Genetic algorithms for VLSI micro-Cell layout area optimization based on binary tree
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Web based personalized university timetable for UiTM students using genetic algorithm / Mohd Radhi Fauzan Jamli and Ahmad Firdaus Ahmad Fadzil
Published 2024“…The proposed approach utilizes genetic algorithms to dynamically produce optimized timetables based on individual student needs, with real-time data scraping from 'iCRESS' ensuring the system stays up to date with the latest course information for accurate timetable generation. …”
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Optimization of ANFIS with GA and PSO estimating α ratio in driven piles
Published 2020“…A learning fuzzy-based algorithm was used to train the ANFIS model in the MATLAB software. …”
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Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi
Published 2019“…This strategy includes a number of components that are a novel approach to clustering generation. In fact a data clustering method is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on our proposed algorithm; which is Enhanced Binary Particle swarm Optimization (EBPSO), (ii) To mine data using various data chunks (windows) and overcome a failure of single clustering. …”
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11
Efficient genetic partitioning-around-medoid algorithm for clustering
Published 2019“…In general, genetic based clustering algorithms showed the ability to reach near global optimal solution. …”
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A Wavelet-Based Particle Swarm Optimization Algorithm for Digital Image Watermarking
Published 2012“…This paper proposes the application of Discrete Wavelet Transform (DWT) into image watermarking by using Particle Swarm Optimization (PSO) which is an evolutionary technique with the stochastic, population-based algorithm for solving this problem. …”
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Multi-mobile agent itinerary planning algorithms for data gathering in wireless sensor networks: a review paper
Published 2017“…The review shows that most of the algorithms used one parameter to find the optimal number of mobile agents in multi-agent itinerary planning without utilizing other parameters. …”
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Multivariate Optimization of Biosynthesis of Triethanolamine-Based Esterquat Cationic Surfactant Using Statistical Algorithms
Published 2011“…The next objective of the current study was to compare the performance of aforementioned algorithms with regard to predicting ability. The investigation of TEA-based esterquat cationic surfactant synthesis was started in a 50 ml scale. …”
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15
Load-Balancing Models for Scheduling Divisible Load on Large Scale Data Grids
Published 2009“…There are some scheduling models, which have been studied, such as Constraint DLT (CDLT), Task Data Present (TDP) and Genetic Algorithm (GA). However, there has been no optimal solution reached. …”
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16
Multilingual Sentiment Analysis From Students Feedback: Optimal Techniques And Resources For Bengali Lingual Data
Published 2024thesis::doctoral thesis -
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Spatial Clustering Algorithm for Time Series Rainfall Data Using X-Means Data Splitting
Published 2017“…Therefore, a clustering algorithm by introducing data transformation using X-means data splitting is proposed to investigate the spatial homogeneity of time series rainfall data. …”
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Development of optimized damage prediction method for health monitoring of ultra high performance fiber-reinforced concrete communication tower
Published 2018“…Therefore, this study aims to develop a new health monitoring system for communication towers based on AdaBoost, Bagging, and RUSBoost algorithms as hybrid algorithm, which can predict the damage by using noisy, random, unstable, and skewed frequency data with high accuracy. …”
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19
Energy-efficient algorithms for dynamic virtual machine consolidation in cloud data centers
Published 2017“…Based on the proposed algorithms, energy consumption can be reduced…”
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On iterative low-complexity algorithm for optimal antenna selection and joint transmit power allocation under impact pilot contamination in downlink 5g massive MIMO systems
Published 2020“…In conclusion, the proposed low-complexity iterative algorithm can be used to maximize the EE based on the maximum transmit power , where the noise power is less than the power of the received pilot sequence.…”
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