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1
New Learning Models for Generating Classification Rules Based on Rough Set Approach
Published 2000“…Recently, different models were used to generate knowledge from vague and uncertain data sets such as induction decision tree, neural network, fuzzy logic, genetic algorithm, rough set theory, and others. …”
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2
Graph-Based Algorithm With Self-Weighted And Adaptive Neighbours Learning For Multi-View Clustering
Published 2024“…To address the noise problem in multi-view data, this study enhances the gbs method and develops a new self-weighted graph multi-view clustering algorithm (swmcan). …”
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3
Hybrid Artificial Bees Colony algorithms for optimizing carbon nanotubes characteristics
Published 2018“…Chemical Vapor Deposition (CVD) is the most efficient method for CNTs production.However,using CVD method encounters crucial issues such as customization,time and cost.Therefore,Response Surface Methodology (RSM) is proposed for modeling and the ABC-βHC is proposed for optimization purpose to address such issues.The selected CNTs characteristics are CNTs yield and quality represented by the ratio of the relative intensity of the D and G-bands (ID/IG).Six case studies are generated from collected dataset including four cases of CNTs yield and one case of ID/IG as single objective optimization problems,while the sixth case represents multi-objective problem.The input parameters of each case are a subset from the set of input parameters including reaction temperature,duration,carbon dioxide flow rate,methane partial pressure,catalyst loading,polymer weight and catalyst weight.The models for the first three case studies were mentioned in the original work.RSM is proposed to develop polynomial models for the output responses in the other three cases and to identi significant process parameters and interactions that could affect the CNTs output responses.The developed models are validated using t-test,correlation and pattern matching.The predictive results have a good agreement with the actual experimental data.The models are used as objective functions in optimization techniques.For multi-objective optimization,this study proposes Desirability Function Approach (DFA) to be integrated with other proposed algorithms to form hybrid techniques namely RSM-DFA,ABC-DFA and ABC-βHC-DFA.The proposed algorithms and other selected well-known algorithms are evaluated and compared on their CNTs yield and quality.The optimization results reveal that ABC-βHC and ABC-βHC-DFA obtained significant results in terms of success rate,required time,iterations,and function evaluations number compared to other well-known algorithms.Significantly,the optimization results from this study are better than the results from the original work of the collected dataset.…”
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4
Automated bilateral negotiation with incomplete information in the e-marketplace.
Published 2011“…In one-side incomplete information problem, comparison between MGT algorithm and smart random trade-offs (SRT) algorithm indicates that MGT outperforms SRT. …”
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5
Optimal planning of photovoltaic distributed generation considering uncertainties using monte carlo pdf embedded MVMO-SH
Published 2021“…The load flow patterns will significantly have affected when uncertain PV generation – load models are considered into the power flow algorithm. …”
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6
Development of collision avoidance warning system for heavy vehicles featuring adaptive minimum safe distance / Airul Sharizli Abdullah
Published 2017“…Finally, the development of prototype microcontroller-based CAWS featuring MSDG activation algorithm has been developed. …”
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7
Improvement on rooftop classification of worldview-3 imagery using object-based image analysis
Published 2019“…The accuracy of each algorithm was evaluated using LibSVM, Bayes network, and Adaboost classifier. …”
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8
A Model Development And Comparison Study On The Microwave Remote Sensing Of Snow Medium Using A Coupled Finite Element Method And Method Of Moment, And The Relaxed Hierarchical Equ...
Published 2022“…The investigatio n is done by integrating two computational techniques, which are the coupled Finite Element Method (FEM) and Method of Moment (MoM) and the Relaxed Hierarchical Equivalent Source Algorithm (RHESA). These CEM generated electric and magnetic fields will be ncorporated with the Dense Medium Phase Amplitude Correction Theory (DMPACT). …”
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Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification
Published 2020“…Nevertheless, AC is not required for LCM if the original multi-spectral image is used. The last phase involves developing a new fusion algorithm using SVM and Fuzzy K-Means Clustering (FKM) algorithms for Sentinel 2 data to enhance LCM accuracy. …”
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10
Classification and visualization on eligibility rate of applicant’s LinkedIn account using Naïve Bayes / Nurul Atirah Ahmad
Published 2023“…This project implements the Naive Bayes algorithm as the classification algorithm. The collected data from LinkedIn profiles then undergoes data preprocessing. …”
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11
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. The employment of automated toolbox is a straightforward process constructed from eight sub-tools to prepare, train, and processes the data. …”
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12
Menu recommendation for Restoran Jannat Saba using Market Basket analysis / Dinie Sorfina Fathanah Kamarul Ariffin
Published 2025“…The FP-Growth algorithm has been employed for its effectiveness in identifying frequent itemsets and association rules in transactional data. …”
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13
Comparative Analysis of Gene Expressed in Trunking and Non-Trunking Metroxylon sagu Leaves Utilizing Transcriptome Sequencing
Published 2023“…The sequence was de novo-assembled using TRINITY software package and the differentially expressed genes (DEGs) were identified using DESeq2 algorithm. …”
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Ant colony optimization algorithm for dynamic scheduling of jobs in computational grid
Published 2012“…In computational grid, job scheduling is one of the main factors affecting grid computing performance. Job scheduling problem is classified as an NP-hard problem.Such a problem can be solved only by using approximate algorithms such as heuristic and meta-heuristic algorithms.Among different optimization algorithms for job scheduling, ant colony system algorithm is a popular meta-heuristic algorithm which has the ability to solve different types of NP-hard problems.However, ant colony system algorithm has a deficiency in its heuristic function which affects the algorithm behavior in terms of finding the shortest connection between edges.This research focuses on a new heuristic function where information about recent ants’ discoveries has been considered.The new heuristic function has been integrated into the classical ant colony system algorithm.Furthermore, the enhanced algorithm has been implemented to solve the travelling salesman problem as well as in scheduling of jobs in computational grid.A simulator with dynamic environment feature to mimic real life application has been development to validate the proposed enhanced ant colony system algorithm. …”
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Fuzzy-based multi-agent approach for reliability assessment and improvement of power system protection
Published 2015“…The second agent is a reliability evaluation agent that uses a recursive algorithm to predict the suitability generator based on the frequency and duration reliability indices in each state while the third agent is the storage and transfer of data between the other two agents. …”
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17
Data depublication using : Hashing algorithm / Naimah Nayan
Published 2019“…This method basically will help to improve the storage capacity and efficiency. The hash value is generated by using hashing algorithm such as Message Digest 5 (MD5) and Secure Hashing Algorithm 1 (SHA-1). …”
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18
A novel peak load shaving algorithm for isolated microgrid using hybrid PV-BESS system
Published 2021“…To evaluate the effectiveness of the algorithm, simulation case studies have been conducted with actual load data and actual PV generation data. …”
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Article -
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Solving economic load dispatch problem using genetic algorithm method / Norliza Kamarulzaman
Published 2009“…Data taken from the test system is analysed as the power system data generation. …”
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20
Automated path testing using the negative selection algorithm
Published 2017“…Negative selection algorithm (NSA) has been used in this paper to generate test data for path testing automatically. …”
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