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  1. 1
    Artificial intelligent integrated into sun-tracking system to enhance the accuracy, reliability and long-term performance in solar energy harnessing

    Artificial intelligent integrated into sun-tracking system to enhance the accuracy, reliability and long-term performance in solar energy harnessing by Tan, Jun You

    Published 2022
    “…The proposed AI algorithm integrates two deep learning models which are object detection algorithm and reinforcement learning. …”
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  2. 2
    Flood mapping based on novel ensemble modeling involving the deep learning, Harris Hawk optimization algorithm and stacking based machine learning

    Flood mapping based on novel ensemble modeling involving the deep learning, Harris Hawk optimization algorithm and stacking based machine learning by Costache R., Pal S.C., Pande C.B., Islam A.R.M.T., Alshehri F., Abdo H.G.

    Published 2025
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  3. 3
    Development of an intelligent system using Kernel-based learning methods for predicting oil-palm yield.

    Development of an intelligent system using Kernel-based learning methods for predicting oil-palm yield. by Md. Sap, Mohd. Noor, Awan, A. Majid

    Published 2005
    “…Intelligent systems based on machine learning techniques, such as classification, clustering, are gaining wide spread popularity in real world applications. …”
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  4. 4
    Optimization of neural network architecture using genetic algorithm for load forecasting

    Optimization of neural network architecture using genetic algorithm for load forecasting by Islam, B.U., Baharudin, Z., Raza, M.Q., Nallagownden, P.

    Published 2014
    “…In this paper, a computational intelligent technique genetic algorithm (GA) is implemented for the optimization of artificial neural network (ANN) architecture. …”
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  5. 5
    Depression prediction using machine learning: a review

    Depression prediction using machine learning: a review by Abdul Rahimapandi, Hanis Diyana, Maskat, Ruhaila, Musa, Ramli, Ardi, Norizah

    Published 2022
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  6. 6
    Detection of surface defects of aluminium extrudants using artificial intelligence

    Detection of surface defects of aluminium extrudants using artificial intelligence by Poon, Chee Kent

    Published 2024
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  7. 7
    Designing a new model for worm response using security metrics

    Designing a new model for worm response using security metrics by Madihah Mohd Saudi, Taib B.M.

    Published 2024
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  8. 8
    Realization of a Hybrid Locally Connected Extreme Learning Machine with DeepID for Face Verification

    Realization of a Hybrid Locally Connected Extreme Learning Machine with DeepID for Face Verification by Wong S.Y., Yap K.S., Zhai Q., Li X.

    Published 2023
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  9. 9
    Pothole detection using UAV with deep learning algorithm for road inspection

    Pothole detection using UAV with deep learning algorithm for road inspection by Abdul Sukor, Nur Sabrina Irwayu, Hashim, Khairil Afendy, Dahlan, Zaki Ahmad

    Published 2024
    “…This paper presents an innovative approach to pothole detection by utilizing Unmanned Aerial Vehicles (UAVs) in combination with a Convolutional Neural Network (CNN) algorithm. The primary aim of this study is to evaluate the effectiveness of the CNN algorithm in detecting road potholes. …”
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  10. 10
    Machine learning using robust AI techniques / Prof. Madya Dr. Nordin Abu Bakar

    Machine learning using robust AI techniques / Prof. Madya Dr. Nordin Abu Bakar by Abu Bakar, Nordin (Prof. Madya Dr.)

    Published 2012
    “…There is a model that studies the social behavior of humans called genetic algorithms (GA). An artificial neural network uses brain as a model to map decisions out of several inputs. …”
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    Research Reports
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  11. 11
    A novel softsign fractional-order controller optimized by an intelligent nature-inspired algorithm for magnetic levitation control

    A novel softsign fractional-order controller optimized by an intelligent nature-inspired algorithm for magnetic levitation control by Ahmad, Mohd Ashraf, Izci, Davut, Ekinci, Serdar, Mohd Tumari, Mohd Zaidi

    Published 2025
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  12. 12
    Artificial intelligent power prediction for efficient resource management of WCDMA mobile network

    Artificial intelligent power prediction for efficient resource management of WCDMA mobile network by Tee Y.K., Tinng S.K., Koh J., David Y.

    Published 2023
    “…The output of SVR will be used by WCDMA mobile network to decide on new service admission. Genetic algorithm (GA) is then applied to form optimal beams to cover all UEs in a cell with minimum power. …”
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  13. 13
    Deep-learning-based detection of missing road lane markings using YOLOv5 algorithm

    Deep-learning-based detection of missing road lane markings using YOLOv5 algorithm by Sophian, Ali, Azmi, Nur Hanisah, Bawono, Ali Aryo

    Published 2021
    “…In this work, preliminary study of the implementation of one of the latest deep learning algorithms, i.e. YOLOv5, has been carried out in the detection and classification of missing road lane markings. …”
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    Proceeding Paper
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  14. 14
    A Novel Path Prediction Strategy for Tracking Intelligent Travelers

    A Novel Path Prediction Strategy for Tracking Intelligent Travelers by Motlagh, Omid Reza Esmaeili

    Published 2009
    “…Genetic algorithm (GA) is then used to train the FCM to be able to replicate the decisional behaviors of the intelligent traveler. …”
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    Thesis
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  15. 15
    Towards paddy rice smart farming: a review on big data, machine learning, and rice production tasks

    Towards paddy rice smart farming: a review on big data, machine learning, and rice production tasks by Rayner Alfred, Joe Henry Obit, Christie Chin Pei Yee, Haviluddin Haviluddin, Yuto Lim

    Published 2021
    “…This paper also presents a framework that maps the activities defined in rice smart farming, data used in data modelling and machine learning algorithms used for each activity defined in the production and post-production phases of paddy rice. …”
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  16. 16
    A preliminary lightweight random forest approach-based image classification for plant disease detection

    A preliminary lightweight random forest approach-based image classification for plant disease detection by Mashitah Ibrahim, Muzaffar Hamzah, Mohammad Fadhli Asli

    Published 2022
    “…Random Forest is a special kind of ensemble learning technique and it turns out to perform very well compared to other classification algorithms such as Support Vector Machines (SVM) and Artificial Neural Networks (ANN). …”
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  17. 17
    Assessing the outcome of Competencies Level from Knowledge-Based Project

    Assessing the outcome of Competencies Level from Knowledge-Based Project by Sungsinlert, Anyamanee

    Published 2008
    “…This project is the new idea to implement the Knowledge Management by applying the concept of Knowledge Map and Social Network Map, which are the basic implementation of Knowledge Management, with Artificial Neural Network (ANN) Algorithm ofArtificial Intelligence System. …”
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  18. 18
    Artificial intelligence (AI) and its application in architecture design: a thematic review

    Artificial intelligence (AI) and its application in architecture design: a thematic review by Jin, Deran, Zairul, Mohd, Salih, Sarah Abdulkareem

    Published 2025
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  19. 19
    RT-DETR-Pothole: lightweight real-time detection transformers for improved road pothole detection

    RT-DETR-Pothole: lightweight real-time detection transformers for improved road pothole detection by Abd Rahman, Mohd Amiruddin

    Published 2025
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  20. 20
    Multi-method diagnosis of CT images for rapid detection of intracranial hemorrhages based on deep and hybrid learning

    Multi-method diagnosis of CT images for rapid detection of intracranial hemorrhages based on deep and hybrid learning by Mohammed, Badiea Abdulkarem, Senan, Ebrahim Mohammed, Al-Mekhlafi, Zeyad Ghaleb, Rassem, Taha Hussein, Makbol, Nasrin M., Alanazi, Adwan Alownie, Almurayziq, Tariq S., Ghaleb, Fuad A., Sallam, Amer A.

    Published 2022
    “…The second proposed system using a hybrid technology consists of two parts: the first part is the GoogLeNet, ResNet-50 and AlexNet models for extracting feature maps, while the second part is the SVM algorithm for classifying feature maps. …”
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