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  1. 1
    Applying machine learning and particle swarm optimization for predictive modeling and cost optimization in construction project management

    Applying machine learning and particle swarm optimization for predictive modeling and cost optimization in construction project management by almahameed, Bader aldeen, Bisharah, Majdi

    Published 2024
    “…This study emphasizes the importance of Machine Learning and Particle Swarm Optimization (PSO) in the context of predictive modeling and cost optimization within the field of construction project management. …”
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  2. 2
    Characterization of water quality conditions in the Klang River Basin, Malaysia using self organizing map and K-means algorithm

    Characterization of water quality conditions in the Klang River Basin, Malaysia using self organizing map and K-means algorithm by Mohd Sharif, Sharifah, Mohd Kusin, Faradiella, Asha’ari, Zulfa Hanan, Aris, Ahmad Zaharin

    Published 2015
    “…This study aimed to determine the spatiotemporal pattern of the water quality data and identifying the sources of pollution in the Klang River Basin. The self organizing map (SOM) combined with the K-means algorithm arranged the data based on the relationships of 25 variables. …”
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  3. 3
    Modified symbiotic organisms search optimization for automatic construction of convolutional neural network architectures

    Modified symbiotic organisms search optimization for automatic construction of convolutional neural network architectures by Jauro, Fatsuma, Abdullahi, Usman Ali, Abdulsalami, Aminu Onimisi, Ibrahim, Adamu Abubakar, Abdullahi, Mohammed, Chiroma, Haruna

    Published 2024
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  4. 4
    Software project estimation with machine learning

    Software project estimation with machine learning by Zakaria, Noor Azura, Ismail, Amelia Ritahani, Yakath Ali, Afrujaan, Mohd Khalid, Nur Hidayah, Zainal Abidin, Nadzurah

    Published 2021
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  5. 5
    Cluster identification and separation in the growing self-organizing map: Application in protein sequence classification

    Cluster identification and separation in the growing self-organizing map: Application in protein sequence classification by Ahmad, N.

    Published 2010
    “…Growing self-organizing map (GSOM) has been introduced as an improvement to the self-organizing map (SOM) algorithm in clustering and knowledge discovery. …”
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  6. 6
    Global and local clustering soft assignment for intrusion detection system: a comparative study

    Global and local clustering soft assignment for intrusion detection system: a comparative study by Mohd Rizal Kadis, Azizi Abdullah

    Published 2017
    “…Clustering is unsupervised learning method that can be used for organizing data by grouping similar features into same group. …”
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  7. 7
    Effective use of artificial intelligence by Malaysian manufacturing firms to enable sustainability 4.0

    Effective use of artificial intelligence by Malaysian manufacturing firms to enable sustainability 4.0 by Chong, Agnes Wen Lin

    Published 2023
    “…In this project, Fornell-Larker parameters are used to test the measurement algorithm for the research's discriminant validity. 380 valid questionnaires returnedback and conducted the calculation of the algorithm's assessment to constructs' validity and realibility assessment, discriminant validity using HTMTand Fornell-Larker approaches. …”
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  8. 8
    Perceptions and practices of blended learning in foreign language teaching at USIM

    Perceptions and practices of blended learning in foreign language teaching at USIM by Suo Yan Ju, Suo Yan Mei

    Published 2024
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  9. 9
    Dynamic role engine and formation control for cooperating agents

    Dynamic role engine and formation control for cooperating agents by S. Hamidreza, Kasaei, S. Mohammadreza, Kasaei, S. Alireza, Kasaei, Mohsen, Taheri

    Published 2009
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  10. 10
    Artificial Neural Network Algorithms to Predict the Compressive Strength of Fly Ash-Based Geopolymers

    Artificial Neural Network Algorithms to Predict the Compressive Strength of Fly Ash-Based Geopolymers by Siaw Hui, Teo

    Published 2025
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  11. 11
    Problem Solving

    Problem Solving by Yahaya, Azizi

    Published 2010
    “…There key steps of problem solving are problem identification, problem definition and representation, strategy construction, organization of information, allocation of resources, monitoring, and evaluation. …”
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  12. 12
    A cognitive mapping approach in real-time haptic rendering interaction for improved spatial learning ability among autistic people / Kesavan Krishnan

    A cognitive mapping approach in real-time haptic rendering interaction for improved spatial learning ability among autistic people / Kesavan Krishnan by Kesavan , Krishnan

    Published 2024
    “…Meanwhile, in the past decade, the use of haptic technology in autism has increased in terms of various disciplines that can assist in improving their learning skills. Nevertheless, the use of haptic technology in terms of spatial learning is still not fully utilized, and this weakens autistic people in the process of learning about their surroundings. …”
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  13. 13
    An automated pipeline for constructing 3D models of monogenean hardparts using machine learning technique for landmarks detection / Teo Bee Guan

    An automated pipeline for constructing 3D models of monogenean hardparts using machine learning technique for landmarks detection / Teo Bee Guan by Teo , Bee Guan

    Published 2019
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  14. 14
    Routing protocols strategies for flying Ad-Hoc network (FANET): Review, taxonomy, and open research issues

    Routing protocols strategies for flying Ad-Hoc network (FANET): Review, taxonomy, and open research issues by Almansor M.J., Din N.M., Baharuddin M.Z., Ma M., Alsayednoor H.M., Al-Shareeda M.A., Al-asadi A.J.

    Published 2025
    Review
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  15. 15
    Neural-tuned PID controller for Point-to-point (PTP) positioning system: model reference approach

    Neural-tuned PID controller for Point-to-point (PTP) positioning system: model reference approach by Wahyudi, Wali Ahmad, Min Htut, Myo

    Published 2009
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  16. 16
    Nonlinear dynamic system identification and control via self-regulating modular neural network

    Nonlinear dynamic system identification and control via self-regulating modular neural network by Kiong, L.C., Rajeswari, M., Rao, M.V.C.

    Published 2003
    “…Self-adaptive learning rates Gradient Descent learning rules are employed in a supervised learning phase. …”
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  17. 17
    Machine Learning based Predictive Modelling of Cybersecurity Threats Utilising Behavioural Data

    Machine Learning based Predictive Modelling of Cybersecurity Threats Utilising Behavioural Data by Ting, Tin Tin, Khiew, Jie Xin, Ali Aitizaz, Lee, Kuok Tiung, Teoh, Chong Keat, Hasan Sarwar

    Published 2023
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  18. 18
    Application of target detection method based on convolutional neural network in sustainable outdoor education

    Application of target detection method based on convolutional neural network in sustainable outdoor education by Yang, Xiaoming, Samsudin, Shamsulariffin, Wang, Yuxuan, Yuan, Yubin, Tengku Kamalden, Tengku Fadilah, Yaakob, Sam Shor Nahar

    Published 2023
    “…Next, the dataset of the specific underwater target image is further constructed. The acquisition system of underwater camera information of manned submersibles is designed through the Single Shot-MultiBox Detector algorithm of deep learning. …”
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  19. 19
    Brain Topographic Mapping of Emotions using Computational Cerebellum

    Brain Topographic Mapping of Emotions using Computational Cerebellum by Yaacob, Hamwira Sakti, Kamaruddin, Norhaslinda, Abdul Rahman, Abdul Wahab

    Published 2013
    “…Such approach employs Cerebellar Model Articulation Controller (CMAC) machine learning algorithm to interpolate and visualize the distribution of activated region during cognitive activities as captured at the scalp. …”
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    Proceeding Paper
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  20. 20
    An ontology-based reasoning framework for reaction mechanisms simulation

    An ontology-based reasoning framework for reaction mechanisms simulation by Alicia Tang, Y., Zain, S., Abdul Rahman, N., Abdullah, R.

    Published 2007
    “…Chemical processes are represented as qualitative models using Qualitative Process Theory (QPT) ontology. The construction of these models is automated based on a set of QR algorithms. …”
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