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A Study on Gradient Boosting Algorithms for Development of AI Monitoring and Prediction Systems by Aziz, N., Akhir, E.A.P., Aziz, I.A., Jaafar, J., Hasan, M.H., Abas, A.N.C.

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IMPLEMENTATION OF BEHAVIOUR BASED NAVIGATION IN A PHYSICALLY CONFINED SITE by ABDUL RAZAK, NUSRAH

“…The behaviour based implementation on the mobile robot managed to find the shortest path with the rate of failure of less than 15%. …”
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Machine failure prediction technique using recurrent neural network long short-term memory-particle swarm optimization algorithm by Rashid, N.A., Abdul Aziz, I., Hasan, M.H.B.

“…This optimized hybrid prediction technique is useful to be implemented in predictive maintenance to predict machine failure. …”
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Lightning Fault Classification for Transmission Line Using Support Vector Machine by Asman S.H., Aziz N.F.A., Kadir M.Z.A.A., Amirulddin U.A.U., Roslan N., Elsanabary A.

“…The most prevalent cause of faults in the power system is lightning strikes, while other causes may include insulator failure, tree or crane encroachment. In this study, two machine learning algorithms, Support Vector Machine (SVM) and k-Nearest Neighbor (kNN), were used and compared to classify faults due to lightning strikes, insulator failure, tree and crane encroachment. …”

Pure intelligent monitoring system for steam economizer trips by Basim Ismail F., Hamzah Abed K., Singh D., Shakir Nasif M.

Prioritisation assessment and robust predictive model for a comprehensive medical equipment maintenance using machine learning techniques / Aizat Hilmi Zamzam by Aizat Hilmi, Zamzam

“…The establishment of a comprehensive maintenance management through a combination of failure analysis and maintenance prioritisation predictive models can be a mechanism for the implementation of predictive maintenance. …”
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Landslide susceptibility mapping: machine and ensemble learning based on remote sensing big data by Kalantar, Bahareh, Ueda, Naonori, Saeidi, Vahideh, Ahmadi, Kourosh, Abdul Halin, Alfian, Shabani, Farzin

“…Next, an ensemble model consisting of all four algorithms is implemented to examine possible performance improvements. …”
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Lightning fault classification for transmission line using support vector machine by Asman, Saidatul Habsah, Ab Aziz, Nur Fadilah, Ab Kadir, Mohd Zainal Abidin, Ungku Amirulddin, Ungku Anisa, Roslan, Nurzanariah, Elsanabary, Ahmed

“…The most prevalent cause of faults in the power system is lightning strikes, while other causes may include insulator failure, tree or crane encroachment. In this study, two machine learning algorithms, Support Vector Machine (SVM) and k-Nearest Neighbor (kNN), were used and compared to classify faults due to lightning strikes, insulator failure, tree and crane encroachment. …”
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Critical Appraisement of Slope Failure Contributing Parameters for Slope Risk Assessment System of Western Sarawak via Multi Statistical Approaches with Artificial Neural Networ... by Nur Hisyam, Ramli

“…The Landslide Susceptibility Model yielded a Root Mean Squared Error of 0.0057 with the hyperparameter of the model being eight neurons in a single hidden layer, a backpropagation learning algorithm, a learning rate of 0.001, and a maximum step of 1E+8. …”
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Corona fault detection in switchgear with extreme learning machine by Ishak S., Koh S.-P., Tan J.-D., Tiong S.-K., Chen C.-P.

“…In this research, a fault detection system is proposed with the implementation of Extreme Learning Machine (ELM). This algorithm is capable to identify faults in switchgear by analyzing the sound wave generated. …”

Location-Based Approach for Route Maintenance in Dynamic Source Routing Protocol by Sjaugi, Muhammad Farhan

“…The objectives of this research are to propose new algorithm to detect route failure as early warning message to the protocol to take further action, and to propose new algorithm for DSR route maintenance to response the early warning message from route failure detection algorithm. …”
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Pure intelligent monitoring system for steam economizer trips by Basim Ismail, F., Hamzah Abed, K., Singh, D., Shakir Nasif, M.

“…Better speed of learning algorithms by using the Extreme Learning Machine has been approved as well. © The authors, published by EDP Sciences, 2017.…”
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Systematic review on ai-blockchain based e-healthcare records management systems by Haddad, Alaa, Habaebi, Mohamed Hadi, Islam, Md. Rafiqul, Hasbullah, Nurul Fadzlin, Zabidi, Suriza Ahmad

“…When smart contracts are used to make decisions and conduct analytics with machine-learning algorithms, the results may be trusted and unquestioned. …”
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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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Systematic review on ai-blockchain based e-healthcare records management systems by Haddad, Alaa, Habaebi, Mohamed Hadi, Islam, Md Rafiqul, Hasbullah, Nurul Fadzlin, Zabidi, Suriza Ahmad

“…When smart contracts are used to make decisions and conduct analytics with machine-learning algorithms, the results may be trusted and unquestioned. …”
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Meta-heuristic approaches for reservoir optimisation operation and investigation of climate change impact at Klang gate dam by Lai, Vivien Mei Yen

“…The Whale Optimisation Algorithm (WOA), Harris Hawks Optimisation (HHO) Algorithm, Lévy Flight WOA (LFWOA) and the Opposition-Based Learning of HHO (OBL-HHO) were proposed to simulate the initial model’s response and optimise the Klang Gate Dam (KGD) release operation with observed inflow, water level (storage), release, and evaporation rate (loss). …”
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Development of warranty management visualisation for automotive aftermarket with integration of AI by Abdul Hamid, Abdul Hamid, Adull Manan, Nor Fazli, Ismail, Mohd Fauzi, Abdul Wahab, Abdul Malek, Khalit, Muhammad Ilham

“…Advanced analytics techniques including Weibull distribution modelling for failure prediction and Python based anomaly detection algorithms were implemented to identify high risk components and unusual claim behaviours. …”
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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush

Integrated artificial intelligence-based classification approach for prediction of acute coronary syndrome by Salari, Nader

“…Although FFBPNN classifier is slightly more accurate than K-NN, there are some advantages such as simple implementability, understandability and interpretability for the latter. …”
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