Search Results - (( peer learning algorithm ) OR ( between work algorithm ))

Comparison between Lamarckian Evolution and Baldwin Evolution of neural network by Taha, Imad, Inazy, Qabas

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An Intelligent Data-Driven Approach for Electrical Energy Load Management Using Machine Learning Algorithms by Akhtar, Shamim, Muhamad Zahim, Sujod, Rizvi, Syed Sajjad Hussain

“…The comprehensive comparative study preparatory to the recommendation of the best candidate out of 24 machine learning algorithms on the SEIL dataset is presented in this work. …”
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Functional link neural network with modified bee-firefly learning algorithm for classification task by Mohmad Hassim, Yana Mazwin

“…This work proposed the implementation of modified Artificial Bee Colony with Firefly algorithm for training the FLNN network to overcome the drawback of BP-learning algorithm. …”
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Evaluating the performance of machine learning techniques in the classification of Wisconsin Breast Cancer by Obaid, Omar Ibrahim, Mohammed, Mazin Abed, Abd Ghani, Mohd Khanapi, A. Mostafa, Salama, AL-Dhief, Fahad Taha

“…Numerous research works have tried to apply the algorithms of machine learning for classifying breast cancer and it was proven by many researchers that machine learning algorithms act preferable in the diagnosing process. …”
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Novice programmers’ emotion and competency assessments using machine learning on physiological data / Fatima Jannat by Fatima, Jannat

“…This work investigates the suitability and effectiveness of machine learning algorithms such as Multinomial Naive Bayes, KNN, Logistic Regression, Decision Tree for predicting levels of arousal intensity among the programmers and LSTM deep learning algorithm to classify the programmers according to their performance. …”
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Q-learning based vertical handover decision algorithm in LTE-A two-tier macrocell-femtocell systems / Ammar Bathich by Bathich, Ammar

“…The proposed handover algorithms are validated using the LTE-Sim simulator under an urban environment. …”
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SLIDING WINDOW TRAINING ALGORITHMS USING MLP-NETWORK FOR CORRELATED AND LOST PACKET DATA by AHMED IZZELDIN, HUZAIFA TAWFEIG

“…The research work also investigates several recursive algorithms including recursive Kalman filter (RKF) and extended Kalman filter (EKF) using extreme learning machine (ELM) and hybrid linear/nonlinear training technique by incorporating the fiee derivative concept. …”
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Comparison of Gradient Boosting Decision Tree Algorithms for CPU Performance by Haithm Haithm, ALSHARI, Abdulrazak Yahya, Saleh, Alper, ODABAŞ

“…This paper aims to compare the performance of CPU implementation of the top three gradient boosting algorithms. We start by explaining how the three algorithms work and the hyperparameters similarities between them. …”
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Automated bilateral negotiation with incomplete information in the e-marketplace. by Jazayeriy, Hamid

“…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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Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process by Ali Al-Assadi, Hayder M. A.

“…Artificial Neural Network (ANN) was selected from Machine Learning Algorithms to be the learning algorithm. ANN is a computer-based simulation of the living nervous system which works quite differently from conventional programming. …”
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Applications of deep learning algorithms for supervisory control and data acquisition intrusion detection system by Balla, Asaad, Habaebi, Mohamed Hadi, Islam, Md Rafiqul, Mubarak, Sinil

“…For each algorithm, prior works have been identified, examined, and described based on their conceptual similarities. …”
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Deep reinforcement learning approaches for multi-objective problem in Recommender Systems by Ee, Yeo Keat

“…In the performance comparison between proposed deep reinforcement learning with evolutionary algorithm, despite one of the variants of evolutionary algorithm has good performance in precision, it has rather weak performance in term of novelty and diversity. …”
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Interpretation of machine learning model using medical record visual analytics by Mohd Khalid, Nur Hidayah, Ismail, Amelia Ritahani, Abdul Aziz, Normaziah

“…Other visual analytic techniques faced the same problem, unreliability to produce strong reason on the output when working with com- plex machine learning models. This paper analyzed several visual analytics ap- proach instantiated in machine learning algorithm for medical record analytics. …”
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Multiobjective deep reinforcement learning for recommendation systems by Ee, Yeo Keat, Mohd Sharef, Nurfadhlina, Yaakob, Razali, Kasmiran, Khairul Azhar, Marlisah, Erzam, Mustapha, Norwati, Zolkepli, Maslina

“…Several works in DRL are available but none has addressed MO RS problems. …”
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Multi-objective deep reinforcement learning for recommendation systems by Keat, Ee Yeo, Mohd Sharef, Nurfadhlina, Yaakob, Razali, Kasmiran, Khairul Azhar, Marlisah, Erzam, Mustapha, Norwati, Zolkepli, Maslina

“…Several works in DRL are available but none has addressed MO RS problems. …”
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Age-based facial recognition using convoluted neural network deep learning algorithm by Julius Yong Wu Jien, Aslina Baharum, Shaliza Hayati A. Wahab, Nordin Saad, Muhammad Omar, Noorsidi Aizuddin Mat Noor

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Deep learning for face detection using matlab by Slim, Salim Adnan

“…High resolution for face detection was approximately 85%. The algorithm was able to distinguish between human and non-human faces. …”
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Operating a reservoir system based on the shark machine learning algorithm by Allawi, Mohammed Falah, Jaafar, Othman, Mohamad Hamzah, Firdaus, Ehteram, Mohammad, Hossain, Md Shabbir, El-Shafie, Ahmed

“…In the current study, the shark machine learning algorithm (SMLA) is proposed to develop an optimal rule for operating the reservoir. …”
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Identifying communities with modularity metric using Louvain and Leiden algorithms by Shibghatullah, Abdul Samad, Hairol Anuar, Siti Haryanti, Abal Abas, Zuraida, Md Yunos, Norhazwani, Setiad, Tedy, Mukhtar, Mohd Fariduddin

“…Performance comparisons between the two and their concept were summarised in detail, as well as the step-by-step learning process of the state-of-the-art algorithms. …”
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User song preferences using preference learning in artificial intelligence by Goh, Beng Jun

“…The most common model is popularity-based model because it is simple and intuitive. That another algorithm is collaborative filtering, this algorithm aims to find similarity between users, songs, and artists. …”
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