Search Results - intelligence valid ((((from algorithm) OR (bees algorithm))) OR (tree algorithm))

Hybrid Artificial Bees Colony Algorithms For Optimizing Carbon Nanotubes Characteristics by Mohammad Jarrah, Mu'ath Ibrahim

“…Optimization is a crucial process to select the best parameters in single and multi-objective problems for manufacturing process.However,it is difficult to find an optimization algorithm that obtain the global optimum for every optimization problem.Artificial Bees Colony (ABC) is a well-known swarm intelligence algorithm in solving optimization problems.It has noticeably shown better performance compared to the state-of-art algorithms.This study proposes a novel hybrid ABC algorithm with β-Hill Climbing (βHC) technique (ABC-βHC) in order to enhance the exploitation and exploration process of the ABC in optimizing carbon nanotubes (CNTs) characteristics.CNTs are widely used in electronic and mechanical products due to its fascinating material with extraordinary mechanical,thermal,physical and electrical properties. …”
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A machine learning approach to predict the activity of smart home inhabitant by Marufuzzaman M., Tumbraegel T., Rahman L.F., Sidek L.M.

A case study of microarray breast cancer classification using machine learning algorithms with grid search cross validation by Mohd Ali, Nursabillilah, Besar, Rosli, Ab Aziz, Nor Azlina

“…Grid search cross validation (CV) is applied for hyperparameter tuning of the algorithms. …”
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A framework of test case prioritisation in regression testing using particle swarm-artificial bee colony algorithm by Ba-Quttayyan, Bakr Salim Abdullah

“…The developed framework, grounded in fault-based testing theory, comprises three key components: inputs, prioritization factors, and a prioritization algorithm. The framework was subsequently verified and validated through expert reviews and experimental testing. …”
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Selective harmonic elimination in cascaded H-bridge multilevel inverter using hybrid APSO algorithm / Mudasir Ahmed by Mudasir , Ahmed

“…The 3rd & 5th harmonics in the 7-level inverter and 3rd to 47th harmonics in the 49-level inverter are chosen to eliminate from respective MLIs. Simulation results show that, at the high-level inverter, the proposed algorithm can easily find the feasible solutions, however, GA, PSO, bee algorithm (BA), and differential evolution (DE) face the difficulty due to less exploration capability. …”
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Data Classification and Its Application in Credit Card Approval by Thai , VinhTuan

“…This project is involved with identification of the available algorithms used in data classification and the implementation of C4.5 decision tree induction algorithm in solving the data classifying task. …”
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Discovering decision algorithm of distance protective relay based on rough set theory and rule quality measure by Othman, Mohamad Lutfi

“…The discovered decision algorithm and association rule from the Rough-Set based data mining had been compared with and successfully validated by those discovered using the benchmarking Decision-Tree based data mining strategy. …”
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Intelligent grading of agarwood essential oil quality using artificial neural network (ANN) / Noratikah Zawani Mahabob by Mahabob, Noratikah Zawani

“…Agarwood oil is a highly traded essential oil with a high price tag. The oil is extracted from the stems of resin-impregnated agarwood trees. …”
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Optimize single line to ground fault detection in distribution grid power system using artificial bee colony by Feryal Ibrahim Jabbar, Feryal Ibrahim Jabbar, Dur Muhammad Soomro, Dur Muhammad Soomro, Mohd Noor Abdullah, Mohd Noor Abdullah, Nur Hanis Mohammad Radzi, Nur Hanis Mohammad Radzi, Mazhar Hussain Baloch, Mazhar Hussain Baloch, Asif Ahmed Rahmoon, Asif Ahmed Rahmoon, Hassan Falah Fakhruldeen, Hassan Falah Fakhruldeen

“…ABC intelligently optimizes many mathematical problems. ABC with network neural artificial intelligence (AI) improves algorithm performance (artificial bee colony network neural (ABCNN)). …”
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Knowledge discovery in distance relay event report: a comparative data-mining strategy of rough set theory with decision tree by Othman, Mohammad Lutfi, Aris, Ishak, Abdullah, Senan Mahmood, Ali, Md. Liakot, Othman, Mohammad Ridzal

“…These rules would then be compared with and validated by benchmarking decision-tree-based data-mining analysis.…”
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Identifying Cyberspace Users� Tendency in Blog Writing Using Machine Learning Algorithms by AbuSalim, S.W.G., Mostafa, S.A., Mustapha, A., Ibrahim, R., Wahab, M.H.A.

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Automatic detection of oil palm tree from UAV images based on the deep learning method by Xinni, Liu, Kamarul Hawari, Ghazali, Fengrong, Han, Izzeldin, I. Mohd

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Transmission loss minimization using SVC based on particle swarm optimization by Jumaat, S.A., Musirin, I., Othman, M.M., Mokhlis, Hazlie

“…The simulations results are compared with those obtained from the Bee Algorithm (BA) technique in the attempt to highlight its merit.…”
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Solar radiation prediction using boosted decision tree regression model: A case study in Malaysia by Jumin E., Basaruddin F.B., Yusoff Y.B.M., Latif S.D., Ahmed A.N.

Enhancing fairness and efficiency in teacher placement based on staff placement model: an intelligent teacher placement selection model for Ministry of Education Malaysia by Shamsul Saniron, Zulaiha Ali Othman, Abdul Razak Hamdan

“…The effectiveness of ITPS was evaluated using five machine learning algorithms: J48, Decision Tree, Naïve Bayes, Random Forest, and K-Nearest Neighbors. …”
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A novel explanatory hybrid artificial bee colony algorithm for numerical function optimization by Jarrah, Muath Ibrahim, Mohamad Jaya, Abdul Syukor, Mohd Abid, Mohd Asyadi Azam, Alqattan, Zakaria N., Azam, Mohd Asyadi, Abdullah, Rosni, Jarrah, Hazim, Abu‑Khadrah, Ahmed Ismail

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Ganoderma boninense classification based on near-infrared spectral data using machine learning techniques by Mas Ira Syafila, Mohd Hilmi Tan, Mohd Faizal, Jamlos, Ahmad Fairuz, Omar, Kamarulzaman, Kamarudin, Mohd Aminudin, Jamlos

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A stacked ensemble deep learning model for water quality prediction / Wong Wen Yee by Wong , Wen Yee

“…The proposed deep learning model renders faster without the use of SMOTE. Any resampling algorithm is not a necessity in the case of this proposed algorithm. …”
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An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM) by Shamim, Akhtar

“…Finally, the proposed algorithms were also validated on another dataset of a university campus in a different region. …”
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Imbalanced multi-class power transformer fault data classification through Edited Nearest Neighbour-Manhattan-Random Forest by R Azmira, Putri Azmira

“…Furthermore, Random Forest is compared to four machine learning algorithms including Support Vector Machine, XGBoost, Convolutional Neural Networks, and Decision Trees. …”
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