Search Results - (( using composition learning algorithm ) OR ( java location based algorithm ))
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Group formation using genetic algorithm
Published 2009“…However, due to lack of programming skills especially in Java programming language and the inability to have meetings frequently among the group members,most of the students’ software project cannot be delivered successfully.To solve this problem, systematic group formation is one of the initial factors that should be considered to ensure that every group consists of quality individuals who are good in Java programming and also to ensure that every group member in a group are staying closer to each other.In this research, we propose a method for group formation using Genetic Algorithms, where the members for each group will be generated based on the students’ programming skill and location of residential colleges.…”
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Monograph -
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Multi-floor indoor location estimation system based on wireless local area network
Published 2007“…The most probable match is selected and returned as estimated location based on Bayesian filtering algorithm. Estimated location is reported as physical location and symbolic location. …”
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Improving the performance of damage repair in thin-walled structures with analytical data and machine learning algorithms
Published 2024“…On the other hand, machine learning (ML) has made it possible to employ a variety of approaches for mechanical and aerospace problems and such significant approach is the repair mechanism and hence ML algorithms used to enhance in the present work. …”
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State-of-the-art ensemble learning and unsupervised learning in fatigue crack recognition of glass fiber reinforced polyester composite (GFRP) using acoustic emission
Published 2023“…This study evaluates the damage progression on glass fiber reinforced polyester composite specimens using different approaches of machine learning. …”
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Potential of soft computing approach for evaluating the factors affecting the capacity of steel–concrete composite beam
Published 2018“…In comparison to the other widely used conventional learning algorithms, the ELM has a much faster learning ability.…”
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Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform
Published 2009“…The development of this architecture is based on several programming language as it involves algorithm implementation on C, parallelization using Parallel Virtual Machine (PVM) and Java for web services development. …”
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Conference or Workshop Item -
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A comparative study of deep learning algorithms in univariate and multivariate forecasting of the Malaysian stock market
Published 2023“…This study aims to develop a univariate and multivariate stock market forecasting model using three deep learning algorithms and compare the performance of those models. …”
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Campus safe: Safeguarding GPS-based Physical Identity and Access Management (PIAM) system with a lightweight Geo-Encryption
Published 2022“…Subsequently, this project embedded with a lightweight Geo-Encryption algorithm to preserve the privacy of real-time GPS location. …”
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Academic Exercise -
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Experimental studies on impact damage location in composite aerospace structures using genetic algorithms and neural networks
Published 2010“…The strain data are used for learning in the Neural Network approach. …”
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NN-Based FECG extraction from the composite abdominal ECG
Published 2008“…According to the output it can be said that the algorithm is working satisfactory on high learning rate and low momentum value. …”
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Proceeding Paper -
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Producer gas composition prediction using artificial neural network algorithm / Mohd Mahadzir Mohammud ... [et al.]
Published 2023“…It is then used to predict the output gas composition from the parameters of a gasification experiment that has been used before in UiTM’s laboratory. …”
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Data Analysis and Machine Learning Algorithms Evaluation for Bioliq AI-based Predictive Tool
Published 2019“…This final year project identified relevant parameters through literature research, analysis and expert interview, and evaluated different machine learning algorithms and identified linear regression as the most applicable and efficient with its R-square of 0.8015, qualifying it to be used for the development of a hybrid model for the AI-based tool for predictive process optimization for chemical plants.…”
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Final Year Project -
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Parametric analysis of critical buckling in composite laminate structures under mechanical and thermal loads: a finite element and machine learning approach
Published 2024“…In summary, this paper delves into the study of the stability of C-section thin-walled composite structures with holes under mechanical and thermal loading conditions using finite element analysis and machine learning studies.…”
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Modelling and optimization of microhardness of electroless Ni-P-TiO2composite coating based on machine learning approaches and RSM
Published 2021“…The microhardness of the electroless Ni-P-TiO2 coated composite was measured and predicted by various machine learning algorithms. …”
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Self learning neuro-fuzzy modeling using hybrid genetic probabilistic approach for engine air/fuel ratio prediction
Published 2017“…A fitness function is proposed to deal with multi-objective problem without weight using a new composition method. The model was compared to other learning algorithms for NFS such as Fuzzy c-means (FCM) and grid partition algorithm. …”
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Performance analysis of support vector machine, Gaussian Process Regression, sequential quadratic programming algorithms in modeling hydrogen-rich syngas production from catalyzed...
Published 2022“…Whereas the best performance in terms of prediction of the syngas composition was obtained using the NLRQM algorithm with an inbuilt SQP and LM algorithms. …”
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