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Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof by Yusof, Yusman

“…From the reviews, it is evident that autonomous system is set to handle finite number of encountered states using finite sequences of actions. In order to learn the optimized states-action policy the self-learning algorithm is developed using hybrid AI algorithm by combining unsupervised weightless neural network, which employs AUTOWiSARD and reinforcement learning algorithm, which employs Q-learning. …”
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Nature inspired meta-heuristic algorithms for deep learning: recent progress and novel perspective by Abubakar, Adamu, Ya’u Gital, Abdulsalam, Chiroma, Haruna, Rana, Nadim, Abdulhamid, Shafi’i, Muhammad, Amina Nuhu, Umar, Aishatu Yahaya

“…In this paper, we present recent progress on the application of nature inspired algorithms in deep learning. The survey pointed out recent development issues, strengths, weaknesses and prospects for future research. …”
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Machine Learning Algorithm for Malware Detection: Taxonomy, Current Challenges, and Future Directions by Gorment N.Z., Selamat A., Cheng L.K., Krejcar O.

“…Finally, to address the related issues that would motivate researchers in their future work, an empirical study was utilized to assess the performance of several machine learning algorithms. � 2013 IEEE.…”

SUDOKU HELPER by Abdul Razak, Muhammad Asyraf

“…In this paper research, author presents an algorithm to provide a tutorial for any Sudoku player who got stuck during the solving process. …”
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A systematic literature review of deep learning neural network for time series air quality forecasting by Zaini N., Ean L.W., Ahmed A.N., Malek M.A.

Performance of correlational filtering and deep learning based single target tracking algorithms / ZhongMing Liao and Azlan Ismail by ZhongMing, Liao, Ismail, Azlan

“…Experiments were conducted on OTB100 and VOT2018 benchmark datasets, and the experimental data obtained were analyzed to derive two visual single-target tracking algorithms with optimal tracking performance. Finally, the future development of tracking algorithms is envisioned.…”
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Recent Automatic Segmentation Algorithms of MRI Prostate Regions: A Review by Khan, Z., Yahya, N., Alsaih, K., Al-Hiyali, M.I., Meriaudeau, F.

“…Besides, a summary of publicly available prostate MRI image datasets is also provided. Finally, the future challenges and limitations of current deep learning-based approaches and suggestions of potential future research are also discussed. …”
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Recent Automatic Segmentation Algorithms of MRI Prostate Regions: A Review by Khan, Z., Yahya, N., Alsaih, K., Al-Hiyali, M.I., Meriaudeau, F.

“…Besides, a summary of publicly available prostate MRI image datasets is also provided. Finally, the future challenges and limitations of current deep learning-based approaches and suggestions of potential future research are also discussed. …”
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A comprehensive review of crop yield prediction using machine learning approaches with special emphasis on palm oil yield prediction by Rashid, Mamunur, Bari, Bifta Sama, Yusri, Yusup, Mohamad Anuar, Kamaruddin, Khan, Nuzhat

“…Due to this developing significance of crop yield prediction, this article provides an exhaustive review on the use of machine learning algorithms to predict crop yield with special emphasis on palm oil yield prediction. …”
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Lexicon-based and immune system based learning methods in Twitter sentiment analysis by Jantan, Hamidah, Drahman, Fatimatul Zahrah, Alhadi, Nazirah, Mamat, Fatimah

“…In future work, the accuracy of proposed model can be strengthened by comparative study with other heuristic based searching algorithms such as genetic algorithm, ant colony optimization, swam algorithms and etc.…”
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Design of a pattern classification system using extreme learning machine by Sakthivel Thangavelu

Design of a pattern classification system using extreme learning machine by Sakthivel Thangavelu

Water Quality Parameter Prediction Using Machine Learning Method by Muhammad Shaiful Bin Abdul Halim

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

“…The challenges facing DL applications in IDS development are also discussed, as well as future research direction and recommendations.…”
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Music Recommender System Using Machine Learning Content-Based Filtering Technique by Foong, Kin Hong

“…Machine Learning allows a system to learn gradually to improve its accuracy in predicting future outcome. …”
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Comparison of supervised machine learning algorithms for malware detection / Mohd Faris Mohd Fuzi ... [et al.] by Mohd Fuzi, Mohd Faris, Mohd Shahirudin, Syamir, Abd Halim, Iman Hazwam, Jamaluddin, Muhammad Nabil Fikri

“…To improve the detection accuracy for future research, it is suggested that the malware dataset be enhanced using several architectures, such as Linux and Android, and use additional supervised and unsupervised machine learning algorithms.…”
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Automated transtibial prosthesis alignment: A systematic review by Khamis T., Khamis A.A., Al Kouzbary M., Al Kouzbary H., Mokayed H., Razak N.A.A., Osman N.A.A.

“…Furthermore, it identifies important limitations in the reviewed studies, serving as a catalyst for future research to address these gaps and explore alternative machine learning algorithms. …”

An improved diagnostic algorithm based on deep learning for ischemic stroke detection in posterior fossa by Muhd Suberi, Anis Azwani

“…The results demonstrate that the performance measure of 90.77% has been recorded for detection rate with average processing time of 1.02 to 1.04 seconds per image. The developed algorithm is reported to be reliable to assist the radiologist in ischemic PF diagnosis which is important for future healthcare needs.…”
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Loan default prediction using machine learning algorithms: a systematic literature review 2020 -2023 by Soomro, Anam, Zakariyah, Habeebullah, Aftab, S.M.A., Muflehi, Mohamad, Shah, Asadullah, Meraj, Syeda

“…Additionally, it identifies Kaggle as a crucial source for research datasets, underlining the importance of accessible and comprehensive data in developing effective predictive models. The paper also outlines future research directions, emphasizing the integration of big data analytics, the application of sophisticated ensemble methods, and the potential of deep learning technologies. …”
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A New Mobile Botnet Classification based on Permission and API Calls by Yusof, M, Saudi, MM, Ridzuan, F

“…As a result, 16 permissions and 31 API calls that are most related with mobile botnet have been extracted using feature selection and later classified and tested using machine learning algorithms. The experimental result shows that the Random Forest Algorithm has achieved the highest detection accuracy of 99.4% with the lowest false positive rate of 16.1% as compared to other machine learning algorithms. …”