Search Results - (( based application learning algorithm ) OR ( _ application acs algorithm ))*

A New Machine Learning-based Hybrid Intrusion Detection System and Intelligent Routing Algorithm for MPLS Network by Ridwan M.A., Radzi N.A.M., Azmi K.H.M., Abdullah F., Ahmad W.S.H.M.W.

“…Machine Learning (ML) is seen as a promising application that offers autonomous learning and provides optimized solutions to complex problems. …”

Adaptive parameter control strategy for ant-miner classification algorithm by Al-Behadili, Hayder Naser Khraibet, Sagban, Rafid, Ku-Mahamud, Ku Ruhana

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Multi-label learning based on positive label correlations using predictive apriori by Al Azaidah, Raed Hasan Saleh

“…Along with that, two algorithms have been constructed by capturing the positive correlations where the first algorithm (MLR-PC) captures the positive global correlations and the second algorithm (MLCBA) proposes an adaption of AC algorithm to handle MLC based on the positive local correlations. …”
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On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing by Kamal Z., Zamli, Alsariera, Yazan A., Nasser, Abdullah B., Alsewari, Abdulrahman A.

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Accuracy of advanced deep learning with tensorflow and keras for classifying teeth developmental stages in digital panoramic imaging by Norhasmira, Mohammad, Anuar Mikdad, Muad, Rohana, Ahmad, Mohd Yusmiaidil, Putera Mohd Yusof

“…Nonetheless, a robust DCNN model was achieved as there is no sign of the model’s over-or under-ftting upon the learning process. Conclusions: The application of digital imaging and deep learning techniques used by the DP-AC and convolutions neural network algorithms to segment and identify premolars provides promising results for semi-automated forensic dental staging in the future…”
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

“…This merit is provided by balancing the exploitation of solution structure and exploration of its appropriate weighting factors through use of a robust and efficient optimization algorithm in learning process of GEP approach. To assess the applicability and accuracy of the proposed method for long-term electrical energy consumption, its estimates are compared with those obtained from artificial neural network (ANN), support vector regression (SVR), adaptive neuro-fuzzy inference system (ANFIS), rule-based data mining algorithm, GEP, linear, quadratic and exponential models optimized by particle swarm optimization (PSO), cuckoo search algorithm (CSA), artificial cooperative search (ACS) algorithm and backtracking search algorithm (BSA). …”
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Predicting 30-day mortality after an acute coronary syndrome (ACS) using machine learning methods for feature selection, classification and visualization by Nanyonga Aziida, Sorayya Malek, Firdaus Aziz, Khairul Shafiq Ibrahim, Sazzli Kasim

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HELM based Reinforcement Learning for Goal Localization by AlDahoul, Nouar, Htike@Muhammad Yusof, Zaw Zaw

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Prediction of Oil Palm Yield Using Machine Learning in the Perspective of Fluctuating Weather and Soil Moisture Conditions: Evaluation of a Generic Workflow by Khan N., Kamaruddin M.A., Ullah Sheikh U., Zawawi M.H., Yusup Y., Bakht M.P., Mohamed Noor N.

“…Current development in precision agriculture has underscored the role of machine learning in crop yield prediction. Machine learning algorithms are capable of learning linear and nonlinear patterns in complex agro-meteorological data. …”

Prediction of oil and gas pipeline failures through machine learning approaches: A systematic review by Al-Sabaeei, A.M., Alhussian, H., Abdulkadir, S.J., Jagadeesh, A.

“…This review article mainly focuses on the novelty of using machine and deep learning techniques, specifically artificial neural networks (ANNs), support vector machines (SVMs) and hybrid machine learning (HML) algorithms, for predicting different pipeline failures in the oil and gas industry. …”
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Compact Convolutional neural network (CNN) based on SincNet for end-to-end motor imagery decoding and analysis by Ahmad Izzuddin, Tarmizi, Mat Safri, Norlaili, Othman, Mohd Afzan

“…In the field of human-computer interaction, the detection, extraction and classification of the electroencephalogram (EEG) spectral and spatial features are crucial towards developing a practical and robust non-invasive EEG-based brain-computer interface. Recently, due to the popularity of end-to-end deep learning, the applicability of algorithms such as convolutional neural networks (CNN) has been explored to achieve the mentioned tasks. …”
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Optimization of Motion Compensated Block-Based DCT Video Compression for Software Implementation by Chen, Soong Der

“…This thesis focuses on ways to improve the existing solutions in the algorithmic and implementation aspects. For the algorithmic aspect, the basic principles of motion compensated DCT block-based compression scheme was studied. …”
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Artificial intelligence (AI) and its application in architecture design: a thematic review by Jin, Deran, Zairul, Mohd, Salih, Sarah Abdulkareem

“…The analysis identified six primary themes: 1) Architecture and Science, which includes research on complex systems, genetic algorithms, and machine learning;2) Architecture and Construction Management, including the development of frameworks that support decision making; architecture and interior design, which includes work on space-planning optimization and furniture and occupant arrangement;3) Architecture Interior Design; 4) Architecture and Urban; which encompasses attempts to develop tools to help design new cities; architectural engineering, where building performance analysis was the most-common AI application; 5) Architectural Engineering; and 6) Design Education and Training, in which AI appears most promising for advancing problem-based learning. …”
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Fuzzy logic inverter controller in photovoltaic applications: Issues and recommendations by Hannan M.A., Ghani Z.A., Hoque M.M., Ker P.J., Hussain A., Mohamed A.

Machine learning application to industrial control systems by Bingi, K., Prusty, B.R., Ibrahim, R.

“…The training of the NN model is based on Levenberg-Marquardt algorithm. Then, for the developed model, a feedback linearization-based controller will be designed. …”
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Social Distancing Detection with Deep Learning Model by Hou Y.C., Baharuddin M.Z., Yussof S., Dzulkifly S.

Development of Image-Based Emotion Recognition using Convolutional Neural Networks by Latif, Atiya, Gunawan, Teddy Surya, Kartiwi, Mira, Arifin, Fatchul, Mansor, Hasmah

“…In recent years, artificial intelligence has been utilized in many applications. One of the prominent applications is detecting emotion from an image, which can help an intelligent automatic response system respond appropriately based on the user’s emotion. …”
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A colour-based building recognition using support vector machine by Mustaffa, Mas Rina, Nasharuddin, Nurul Amelina, Abdullah, Lili Nurliyana, Loh, Weng Yee

“…These feature values are later used to train the system using supervised learning algorithm, which is Support Vector Machine (SVM). …”
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Feature selection and optimal neural network algorithm for the state of charge estimation of lithium-ion battery for electric vehicle application by Hossain Lipu M.S., Hannan M.A., Hussain A.

Real-time vehicle counting using custom YOLOv8n and DeepSORT for resource-limited edge devices by Saadeldin, Abuelgasim, Rashid, Muhammad Mahbubur, Shafie, Amir Akramin, Hasan, Tahsin Fuad

“…Recently, there has been a significant increase in the use of deep learning and low-computing edge devices for analysis of video-based systems, particularly in the field of intelligent transportation systems (ITS). …”
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