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1
Neural network algorithm development for Ion Sensitive Field Effect Transistor (ISFET) sensor / Muhammad Nasrul Hakim Adenan
Published 2013“…Backpropagation is used as the learning method of ANN model. The algorithm will be developed in MATLAB. …”
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Neural network algorithm development for Ion Sensitive Field Effect Transistor (ISFET) sensor: article / Muhammad Nasrul Hakim Adenan and Maizatul Zolkapli
Published 2013“…Backpropagation is used as the learning method of ANN model. The algorithm will be developed in MATLAB. …”
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Poverty risk prediction based on socioeconomic factors using machine learning approach
Published 2025“…This study seeks to develop a predictive model of measuring poverty risk using socioeconomic factors based on a machine learning framework. …”
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Talent classification using support vector machine technique / Hamidah Jantan, Norazmah Mat Yusof and Mohd Hanapi Abdul Latif
Published 2014“…Data mining is a widely used approach for knowledge discovery in machine learning. …”
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Research Reports -
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An artificial immune system model as talent performance predictor / Siti ‘Aisyah Sa’dan, Hamidah Jantan and Mohd Hanapi Abdul Latif
Published 2016“…Immune based algorithm is part of bio-inspired algorithms elicits theories which can act as an inspiration for computer-based solutions. …”
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A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing
Published 2024“…While the firefly algorithm solution is superior, it has a higher time complexity compared to other algorithms used when there are more hidden layers and neurons. …”
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7
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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8
Optimal power flow based on fuzzy linear programming and modified Jaya algorithms
Published 2017“…In the proposed novel QOJaya algorithm, an intelligence strategy, namely, quasi-oppositional based learning (QOBL) is incorporated into the basic Jaya algorithm to enhance its convergence speed and solution optimality. …”
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Pothole detection using UAV with deep learning algorithm for road inspection
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Security alert framework using dynamic tweet-based features for phishing detection on twitter
Published 2019“…Many phishing detection methods, ranging from blacklists, heuristics and visual similarity to machine learning are used to detect phishing attacks for spam emails, machine learning approaches achieve the best phishing email detection results. …”
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11
Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm
Published 2025“…After classifying the time set using the canopy with the K-means algorithm and the vector representation weighted by factors, the clustering impact is assessed using purity, precision, recall, and F value. …”
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Successor selection for Ant Colony Optimization technique algorithm / Muhammad Iskandar Isman
Published 2017“…Selecting a successor is used subjective criteria to evaluate in higher learning of successor based on the following factors. …”
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13
Investigating optimal smartphone placement for identifying stairs movement using machine learning
Published 2023“…The data was trained against 6 machine learning algorithms namely Decision Tree, Logistic Regression, Naive Bayes, Random Forest, Neural Networks and KNN. …”
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A Multi-Criteria Recommendation Technique for Personalized Tourism Experiences
Published 2025“…Using ResNet, the algorithm can learn more complex and nuanced patterns in the data, leading to more accurate recommendations. …”
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15
Theory-guided machine learning for predicting and minimising surface settlement caused by the excavation of twin tunnels / Chia Yu Huat
Published 2024“…This dataset, alongside key parameters like cover-to-depth ratio, pillar width, soil stiffness, cohesion, friction angle, and overburden-to-face pressure ratio, integrates into a machine learning framework using a theory-guided approach. …”
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Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed
Published 2012“…Multilayer Feedforward Back Propagation (MLFFBP) was used. Among the available learning algorithms in the Neural Network Toolbox of MATLAB, three algorithms, gradient descent back propagation (TRAINGD), gradient descent with adaptive learning rule back propagation (TRAINGDA) and the Levenberg-Marquardt (TRAINLM) were studied. …”
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17
CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING
Published 2017“…In this research work, a modified backpropagation neural network is combined with a modified chaos-search genetic algorithm for STLF of one day and a week ahead. Multiple modifications are carried out on the conventional back-propagation (BP) algorithm such as, improvements in the momentum factor and adaptive learning rate. …”
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18
Modeling a problem solving approach through computational thinking for teaching programming / Zebel Al Tareq
Published 2021“…The problem-based and the game-based programming workshops utilizing our problem-solving model using sorting algorithms were the experimental groups. …”
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Machine learning techniques for reference evapotranspiration and rice irrigation requirements prediction: a case study of Kerian irrigation scheme, Malaysia
Published 2025“…ETo and rice irrigation requirements were first estimated using FAO Penman–Monteith (FAO-PM56) and the water balance model, respectively, and the obtained results were used as reference values in the machine learning algorithms. …”
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Article -
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Box-jenkins and genetic algorithm hybrid model for electricity forecasting system
Published 2005“…By adopting the GA blind search, the algorithm combines searching techniques and their capabilities to learn about the relationship of the pattern-recognition of the past data. …”
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