Search Results - (( site selection ((method algorithm) OR (_ algorithm)) ) OR ( java application based algorithm ))
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Failure detection analysis of grid-connected photovoltaic systems in tropical climate region / Nurmalessa Muhammad @ Atan
Published 2020“…Two additional sites from T&C of the FiT scheme were used for the verification of the new developed FD algorithm. …”
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Thesis -
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Mobile agent routing for query retrieval using genetic algorithm
Published 2004“…Mobile agents often have a task to collect data from several predefined sites.This should be done in an efficient way by minimizing the elapsed time.Usually these agents only know the list of sites but not the distances between them.This paper proposes a method to minimize a network routing time taken by the mobile agents to collect information from different sites using genetic algorithm (GA).The mobile agents repeat travelling over short routes and avoid longer ones.Mobile agents for query retrieval have used the GA to select the best routes that minimize the query retrieval time.The result shows that the proposed method provides good time minimization in retrieving the query results by the mobile agents based on different GA parameters.…”
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Integrated Features by Administering the Support Vector Machine of Translational Initiations Sites in Alternative Polymorphic Context
Published 2012“…Many algorithms and methods have been proposed for classification problems in bioinformatics. …”
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Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed
Published 2012“…In recent years soft computing methods like fuzzy logic and genetic algorithm are being used in modeling complex processes of hydrologic events. …”
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Optimized placement, sizing, and selection of distributed generation using the salp swarm algorithm
Published 2025“…The salp swarm algorithm (SSA) was introduced as a method for efficiently selecting the optimal location, size, and type of distributed generation (DG) in a distribution system. …”
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A novel framework for identifying twitter spam data using machine learning algorithms
Published 2020“…By initializing data pre-processing for clean-up, noise removal, and unpredictable unfinished data, reducing the number of features in the tweet dataset using mutual information is the study's methods. The feature selection is introduced to select the most important from the extracted high-dimensional best features and feed the selected features into the minimum Redundancy and Maximal Relevance algorithm and apply random forest for classification. …”
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Road condition assessment by OBIA and feature selection techniques using very high-resolution WorldView-2 imagery
Published 2016“…The chi-square algorithm outperformed SVM and RF techniques. The classification result based on CHI algorithm achieved an overall accuracy of 83.19% for the training image (first site). …”
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Network routing by mobile agents for image retrieval using fuzzy genetic algorithms
Published 2005“…Usually these agents only know the list of sites but not the distance s between them. This research proposes a method to minimize a network routing time taken by the mobile agents using genetic algorithm (GA) to collect query datasets from different hosts from the World Wide Web. …”
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Monograph -
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Route selection of mobile agent for query retrieval using GA
Published 2004“…Usually these agents only know the list of sites but not the distances between them. This paper proposes a method to minimize a network routing time taken by the mobile agents to collect information from different sites using genetic algorithm (GA). …”
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Systematic Literature Review for Lightweight Authentication Algorithm in the IOT
Published 2024journal::journal article -
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An Optimized ANN Measure-Correlate-Predict Method for Long-term Wind Prediction in Malaysia
Published 2023Conference Paper -
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Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm
Published 2023“…(SESB) to reduce their distribution loss, estimated around 15% at present in Sabah State, Malaysia. The hybrid algorithm is able to preselect customers to be inspected on-site for abnormalities or potential fraud according to their consumption patterns. …”
Conference Paper -
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Optimizing palm oil biomass collection: genetic algorithm approaches in solving location-routing problem
Published 2025“…To achieve these objectives, the research employs genetic algorithm (GA) approaches, incorporating innovative strategies, namely automated mutation operator selection (AMOS) and elite child population (ECP). …”
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Extreme air pollutant data analysis using classical and Bayesian approaches
Published 2015“…MTM algorithm is an extension of MH algorithm, designed to improve the convergence of MH algorithm by performing parallel computation. …”
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Thesis -
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RSA Encryption & Decryption using JAVA
Published 2006“…The implementation of this project will be based on Rapid Application Design Methodology (RAD) and will be more focusing on research and finding, ideas and the implementation of the algorithm, and finally running and testing the algorithm. …”
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Final Year Project -
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Spatial Data Mining Model For Landfill Sites Suitability Mapping Based On Neural Networks And Multivariate Analysis
Published 2017“…Hybrid neural network was utilized as an evaluation method to select the optimal selection method and optimal training algorithm. …”
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Optimized techniques for landslide detection and characteristics using LiDAR data
Published 2018“…Also, six techniques: Ant Colony Optimization (ACO), Gain Ratio (GR), Particle Swarm Optimization (PSO) and Genetic Algorithm (GA), Random forest (RF), and Correlation-based Feature Selection (CFS) were used for the feature selection. …”
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Comparative Analysis Using Bayesian Approach To Neural Network Of Translational Initiation Sites In Alternative Polymorphic Contex
Published 2012“…The objectives of this paper are to develop useful algorithms and to build a new classification model for the case study.The first approach of neural network includes training on algorithms of Resilient Backpropagation,Scaled Conjugate Gradient Backpropagation and Levenberg-Marquardt.The outputs are used in comparison with Bayesian Neural Network for efficiency comparison.The results showed that Resilient Backpropagation have the consistency in all measurement but performs less in accuracy.In second approach,the Bayesian Classifier_01 outperforms the Resilient Backpropagation by successfully increasing the overall prediction accuracy by 16.0%.The Bayesian Classifier_02 is built to improve the accuracy by adding new features of chemical properties as selected by the Information Gain Ratio method,and increasing the length of the window sequence to 201.The result shows that the built model successfully increases the accuracy by 96.0%.In comparison,the Bayesian model outperforms Tikole and Sankararamakrishnan (2008) by increasing the sensitivity by 10% and specificity by 26%. …”
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