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Learning Algorithm effect on Multilayer Feed Forward Artificial Neural Network performance in image coding by Mahmoud, Omer, Anwar, Farhat, Salami, Momoh Jimoh Emiyoka

“…One of the essential factors that affect the performance of Artificial Neural Networks is the learning algorithm. …”
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Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process by Ali Al-Assadi, Hayder M. A.

“…The design network is trained by presenting several target machining data that the network must learn according to a learning rule (algorithm). …”
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Railway shortest path planner application using ant colony optimization algorithm / Muhammad Hassan Firdaus Ruslan by Ruslan, Muhammad Hassan Firdaus

“…Railway system consists of complicated, most often than not, confusing routes. As train networks expand, routes complexity increases thus indirectly affecting accustomed user. …”
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Speech enhancement using deep neural network based on mask estimation and harmonic regeneration noise reduction for single channel microphone by Md Jamal, Norezmi

“…Moreover, the task of removing noises without causing speech distortion is also challenging, in which the quality and intelligibility of speech are affected. In order to overcome these issues, a supervised Deep Neural Network (DNN) algorithm predicted constrained Wiener Filter (cWF) target mask algorithm based on extracted Gammatone filter bank power spectrum (GF-TF) features and trained model is developed. …”
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Development of heuristic task scheduling algorithm in cloud computing by Diallo, Laouratou, Hassan Abdalla Hashim, Aisha, Olanrewaju, Rashidah Funke

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Recognition of isolated elements picture using backpropagation neural network / Melati Sabtu by Sabtu, Melati

“…This project is developed to train the computer programs to recognize objects in the pictures. …”
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Analyzing CT images for detecting lung cancer by applying the computational intelligence-based optimization techniques by Pethuraj, Mohamed Shakeel, Mohd Aboobaider, Burhanuddin, Salahuddin, Lizawati

“…To attain the problem statement, an lung cancer identification system is developed with the help of a meta-heuristic algorithm. …”
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Development of lung cancer prediction system using meta-heuristic optimized deep learning model by Mohamed Shakeel, Pethuraj

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Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy by Ganesh , Krishnasamy

“…An efficient iterative algorithm is developed to optimize the objective function of the proposed algorithm since it is non-smooth and difficult to solve. …”
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Physics-guided deep neural network to characterize non-Newtonian fluid flow for optimal use of energy resources by Kumar, A., Ridha, S., Narahari, M., Ilyas, S.U.

“…In this research, a novel algorithm (Herschel Bulkley Network) is introduced to simulate the non-Newtonian fluid flow in a pipe using data redundant deep neural network (DNN) for fully developed, laminar, and incompressible flow conditions. …”
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Enhanced mechanism to handle missing data of Hadith classifier by Aldhlan, Kawther A., Zeki, Ahmed M., Zeki, Akram M.

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Prediction of UiTM student academic performance using Naive Bayes algorithm / Muhammad Irfan Zahin Jailani by Jailani, Muhammad Irfan Zahin

“…This paper proposes a predictive system using the Naive Bayes algorithm to solve the pressing issue of low academic performance among students at Universiti Teknologi MARA (UiTM).The study underlines a variety of factors affecting student outcomes while highlighting the significance of effective academic performance. …”
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An Efficient IDS Using Hybrid Magnetic Swarm Optimization in WANETs by Sadiq, Ali Safaa, Alkazemi, Basem, Mirjalili, Seyedali, Ahmed, Noraziah, Khan, Suleman, Ali, Ihsan, Pathan, Al-Sakib Khan, Ghafoor, Kayhan Zrar

“…Our developed algorithm works in extracting the most relevant features that can assist in accurately detecting the network attacks. …”
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An efficient IDS using hybrid Magnetic swarm optimization in WANETs by Sadiq, Ali Safa, Alkazemi, Basem Y., Mirjalili, Seyedali, Noraziah, Ahmad, Khan, Suleman, Ihsan, Ali, Pathan, Al-Sakib Khan, Ghafoor, Kayhan Zrar

“…Our developed algorithm works in extracting the most relevant features that can assist in accurately detecting the network attacks. …”
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Deep learning detector for pests and plant disease recognition by Ileladewa, Oluwatimilehin Adekunle

“…The goal of this project is to develop a framework that can classify the class of a plant, and detect areas of the plant leaf already affected by diseases, and eventually deploy the framework on a mobile application. …”
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Particle swarm optimization for neural network learning enhancement by Abdull Hamed, Haza Nuzly

“…Two programs have been developed; Particle Swarm Optimization Feedforward Neural Network (PSONN) and Genetic Algorithm Backpropagation Neural Network (GANN). …”
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Hardware development of autonomous mobile robot based on actuating lidar by Mohd Romlay, Muhammad Rabani, Mohd Ibrahim, Azhar, Toha, Siti Fauziah, Rashid, Muhammad Mahbubur, Ahmad, Muhammad Syahmi

“…From here, the extracted values are implied on k-NN, Decision Tree and CNN training algorithm. The final result shows promising potential with 91% prediction when implemented on the Decision Tree algorithm based on our proposed system of a single actuating LiDAR sensor.…”
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PV fault classification: Impact on accuracy performance using feature extraction in random-forest cross validation algorithm by Muhamad Zahim, Sujod, Siti Nor Azlina, Mohd Ghazali, Mohd Fadzil, Abdul Kadir, Al-Shetwi, Ali Qasem

“…In this process, each simulated fault that are line-line faults (LLF), open-circuit faults (OCF), ground faults (GF) and partial shading (PS) dataset was divided, with 80% allocated for training and 20% for testing purposes. As the results, all SFDC models (small, medium, large-scale) developed have achieved 100% accuracy for all fault types in training simulations. …”
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Investigation And Development Of Forensic Mean-Based Adaptive Background Correction Algorithm (Mabca) For Visual Enhancement Of Bloodstains, Seminal Stains And Fingerprints by Lee, Wee Chuen

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Base drag estimation in suddenly expanded supersonic flows using backpropagation genetic and recurrent neural networks by Jaimon, Dennis Quadros, Prashanth, T., Khan, Sher Afghan

“…Due to the requirement of massive data for batch mode training, the data required for training was achieved using the response equations developed through response surface methodology. …”
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