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A modified Q-learning path planning approach using distortion concept and optimization in dynamic environment for autonomous mobile robot by Low, Ee Soong, Ong, Pauline, Low, Cheng Yee

“…To this end, three different modes are introduced into the IQL algorithm, namely the normal mode, the distortion mode, and the optimization mode. …”
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A modified Q-learning path planning approach using distortion concept and optimization in dynamic environment for autonomous mobile robot by Ee Soong Low, Ee Soong Low, Pauline Ong, Pauline Ong, Cheng Yee Low, Cheng Yee Low

“…To this end, three different modes are introduced into the IQL algorithm, namely the normal mode, the distortion mode, and the optimization mode. …”
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A modified Q-learning path planning approach using distortion concept and optimization in dynamic environment for autonomous mobile robot by Ee Soong Low, Ee Soong Low, Pauline Ong, Pauline Ong, Cheng Yee Low, Cheng Yee Low

“…To this end, three different modes are introduced into the IQL algorithm, namely the normal mode, the distortion mode, and the optimization mode. …”
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Optimal Tuning of Fractional Order Sliding Mode Controller for PMSM Speed Using Neural Network with Reinforcement Learning by Zahraoui Y., Zaihidee F.M., Kermadi M., Mekhilef S., Alhamrouni I., Seyedmahmoudian M., Stojcevski A.

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Optimal variational mode decomposition and integrated extreme learning machine for network traffic prediction by Jinmei Shi, Yu-Beng Leau, Kun Li, Huandong Chen

“…Given this context, this paper proposes a network traffic prediction mechanism based on optimized Variational Mode Decomposition (VMD) and Integrated Extreme Learning Machine (ELM). …”
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Prediction of payment method in convenience stores using machine learning by Pratondo, Agus, Novianty, Astri, Pudjoatmodjo, Bambang

“…This study explores the application of machine learning techniques, specifically the Random Forest algorithm, to predict payment modes in the context of the Indonesian community. …”
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Comparative study on job scheduling using priority rule and machine learning by Murad, Saydul Akbar, Zafril Rizal, M Azmi, Abu Jafar, Md Muzahid, Al-Imran, Md.

“…We’ve achieved better for SJF and a decent machine learning algorithm outcome as well.…”
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Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection by Tubishat, Mohammad, Idris, Norisma, Shuib, Liyana, Abushariah, Mohammad A.M., Mirjalili, Seyedali

“…An improved version of Salp Swarm Algorithm (ISSA) is proposed in this study to solve feature selection problems and select the optimal subset of features in wrapper-mode. …”
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A new hybrid fuzzy ARTMAP and radial basis function neural network with online pruning strategy by Leow S.Y., Wong S.Y., Yap K.S., Yap H.J.

Optimization of blood vessel detection in retina images using multithreading and native code for portable devices by Tran, Duc Ngoc, Hussin, Fawnizu Azmadi, Yusoff, Mohd Zuki

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Performance evaluation of real-time multiprocessor scheduling algorithms by Alhussian, H., Zakaria, N., Abdulkadir, S.J., Fageeri, S.O.

“…These results suggests that optimal algorithms may turn to be non-optimal when practically implemented, unlike USG which reveals far less scheduling overhead and hence could be practically implemented in real-world applications. …”
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New Learning Models for Generating Classification Rules Based on Rough Set Approach by Al Shalabi, Luai Abdel Lateef

“…So, the application of the theory as part of the learning models was proposed in this thesis. Two different models for learning in data sets were proposed based on two different reduction algorithms. …”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Dheyab, Saad Ahmed, Mohammed Abdulameer, Shaymaa, Mostafa, Salama A

“…This model relies mainly on dimensionality reduction and machine learning algorithms. The principal component analysis (PCA) and the linear discriminant analysis (LDA) techniques perform the dimensionality reduction in individual and hybrid modes to process and improve the data. …”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Dheyab, Saad Ahmed, Mohammed Abdulameer, Shaymaa, Mostafa, Salama A.

“…This model relies mainly on dimensionality reduction and machine learning algorithms. The principal component analysis (PCA) and the linear discriminant analysis (LDA) techniques perform the dimensionality reduction in individual and hybrid modes to process and improve the data. …”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Ahmed Dheyab, Saad, Mohammed Abdulameer, Shaymaa, Mostafa, Salama A

“…This model relies mainly on dimensionality reduction and machine learning algorithms. The principal component analysis (PCA) and the linear discriminant analysis (LDA) techniques perform the dimensionality reduction in individual and hybrid modes to process and improve the data. …”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Dheyab, Saad Ahmed, Mohammed Abdulameer, Shaymaa, Mostafa, Salama

“…This model relies mainly on dimensionality reduction and machine learning algorithms. The principal component analysis (PCA) and the linear discriminant analysis (LDA) techniques perform the dimensionality reduction in individual and hybrid modes to process and improve the data. …”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Dheyab, Saad Ahmed, Mohammed Abdulameer, Shaymaa, Mostafa, Salama

“…This model relies mainly on dimensionality reduction and machine learning algorithms. The principal component analysis (PCA) and the linear discriminant analysis (LDA) techniques perform the dimensionality reduction in individual and hybrid modes to process and improve the data. …”
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Route Optimization System by Zulkifli, Abdul Hayy

“…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
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Fostering motivation in TVET students: the role of learner-paced segments and computational thinking in digital video learning by Wan Nor Ashiqin Wan Ali, Wan Ahmad Jaafar Wan Yahaya, Syed Zulkarnain Syed Idrus, Mohd Noorul Fakhri Yaacob

“…Content delivered in the learner-paced mode allows students to progress through segments at their own pace, while the system-paced mode follows a fixed sequence. …”
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SLIDING WINDOW TRAINING ALGORITHMS USING MLP-NETWORK FOR CORRELATED AND LOST PACKET DATA by AHMED IZZELDIN, HUZAIFA TAWFEIG

“…This thesis gives a systematic investigation of various MLP learning mainly Sliding Window (SW) learning mode which is treated as the adaptation of offline algorithms into online application Consequently this thesis reviews various offline algorithms including: batch backpropagation, nonlinear conjugate gradient, limited memory and full-memory Broyden, Fletcher, Goldfarb and Shanno algorithms and different forms of the latest proposed bimary ensemble learning. …”
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