Search Results - (( intelligence system learning algorithm ) OR ( intelligence self using algorithm ))

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  1. 1
    Intelligent agent for e-commerce using genetic algorithm / Kok Sun Sun

    Intelligent agent for e-commerce using genetic algorithm / Kok Sun Sun by Kok , Sun Sun

    Published 2000
    “…In order to develop an intelligent agent, various programming techniques are used in achieving the property of self learning, information retrieval and searching algorithm. …”
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  2. 2
    Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof

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

    Published 2019
    “…By integrating both algorithms, a system will be able to acquire knowledge, learn, record and recall experience thus enables an autonomous system to self-learn. …”
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  3. 3
    Self-driving car with Artificial Intelligence (AI) technology / Asrul Amin Mohd Isa ... [et al.]

    Self-driving car with Artificial Intelligence (AI) technology / Asrul Amin Mohd Isa ... [et al.] by Mohd Isa, Asrul Amin, Hasnan, Aimuni Aina, Hashim, Zuyyin, Othman, Jamal

    Published 2023
    “…It is based on the use of sensors, actuators, sophisticated algorithms, machine learning systems, and robust processors. …”
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  4. 4
    An intelligent framework for modelling and active vibration control of flexible structures

    An intelligent framework for modelling and active vibration control of flexible structures by Mohd. Hashim, Siti Zaiton

    Published 2004
    “…The first controller design is formulated so as to allow on-line modeling, controller design and implementation and thus, yield a self-tuning control algorithm. Performance of the AVC algorithm is assessed based on parametric design techniques, using RLS and GAS, and non-parametric design techniques, using MLP-NN and ANFIS in the suppression of vibration of the flexible structures. …”
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  5. 5
    Lithium-ion Battery State of Charge Estimation Method Using Optimized Deep Recurrent Neural Network Algorithm

    Lithium-ion Battery State of Charge Estimation Method Using Optimized Deep Recurrent Neural Network Algorithm by Lipu M.S.H., Hannan M.A., Hussain A., Saad M.H.M., Ayob A., Muttaqi K.M.

    Published 2023
    “…Alumina; Aluminum oxide; Backpropagation; Battery management systems; Bioluminescence; Charging (batteries); Cobalt compounds; Deep neural networks; Genetic algorithms; Ions; Lithium compounds; Machine learning; Nickel oxide; Radial basis function networks; Recurrent neural networks; Back-propagation neural networks; Computation intelligences; Electrochemical batteries; Firefly algorithms; Manganese-cobalt oxides; Radial basis function neural networks; Self-learning capability; State of charge; Lithium-ion batteries…”
    Conference Paper
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  6. 6
    A pond-surface-based Biofloc-farm health-monitoring system for African catfish using deep learning methods

    A pond-surface-based Biofloc-farm health-monitoring system for African catfish using deep learning methods by Nizam Nordin

    Published 2022
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    Academic Exercise
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  7. 7
    The development of a tracking algorithm for ambulance detection using squaring of RGB and HSV color processing techniques

    The development of a tracking algorithm for ambulance detection using squaring of RGB and HSV color processing techniques by Mohammad Syawaludin Syafiq, Hassan

    Published 2016
    “…It does not have an intelligent sensor to self-learn the road conditions and number of vehicles so that the controller will react based on the traffic information at a particular intersection. …”
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  8. 8
    Nature-Inspired cognitive evolution to play Ms. Pac-Man

    Nature-Inspired cognitive evolution to play Ms. Pac-Man by Tse, Guan Tan, Jason Teo, Patricia Anthony

    Published 2011
    “…The focus of this research is to explore the hybridization of nature-inspired computation methods for optimization of neural network-based cognition in video games, in this case the combination of a neural network with an evolutionary algorithm. In essence, a neural network is an attempt to mimic the extremely complex human brain system, which is building an artificial brain that is able to self-learn intelligently. …”
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  9. 9
    Teaching and learning via chatbots with immersive and machine learning capabilities

    Teaching and learning via chatbots with immersive and machine learning capabilities by Nantha Kumar Subramaniam

    Published 2019
    “…These chatbots acquired its intelligence through a hybrid approach that combines pattern-matching technique and machine learning algorithm in order to formulate its responses. …”
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  10. 10
    Utilisation of Exponential-Based Resource Allocation and Competition in Artificial Immune Recognition System

    Utilisation of Exponential-Based Resource Allocation and Competition in Artificial Immune Recognition System by Hormozi, Shahram Golzari

    Published 2011
    “…There has been a rapid growth in using Artificial Immune Systems for applications in data mining and computational intelligence recently. …”
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  11. 11
    Review of intelligence for additive and subtractive manufacturing: current status and future prospects

    Review of intelligence for additive and subtractive manufacturing: current status and future prospects by Rahman, M Azizur, Saleh, Tanveer, Jahan, Muhammad Pervej, McGarry, Conor, Chaudhari, Akshay, Huang, Rui, Tauhiduzzaman, M, Ahmed, Afzal, Mahmud, Abdullah Al, Bhuiyan, Md. Shahnewaz, Khan, Md Faysal, Alam, Md. Shafiul, Shakur, Md Shihab

    Published 2023
    “…Similarly, AM product quality can be improved through the online monitoring of melt pool and defect formation using suitable sensing devices followed by process control using machine learning (ML) algorithms. …”
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  12. 12
    Feature selection optimization using hybrid relief-f with self-adaptive differential evolution

    Feature selection optimization using hybrid relief-f with self-adaptive differential evolution by Zainudin, Muhammad Noorazlan Shah, Sulaiman, Md. Nasir, Mustapha, Norwati, Perumal, Thinagaran, Ahmad Nazri, Azree Shahrel, Mohamed, Raihani, Abd Manaf, Syaifulnizam

    Published 2017
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  13. 13
    An improved negative selection algorithm based on the hybridization of cuckoo search and differential evolution for anomaly detection

    An improved negative selection algorithm based on the hybridization of cuckoo search and differential evolution for anomaly detection by Ayodele Nojeem, Lasisi

    Published 2018
    “…The V-Detectors algorithm depends greatly on the random detectors generated in monitoring the status of a system. …”
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  14. 14
    Permodelan Rangkaian Neural Buatan Untuk Penilaian Kendiri Teknologi Maklumat Guru Pelatih

    Permodelan Rangkaian Neural Buatan Untuk Penilaian Kendiri Teknologi Maklumat Guru Pelatih by Hashim, Asman

    Published 2001
    “…Data containing eleven predictive variables was used to train and test neural network model. The research procedures chosen were the multi-layered perceptron with back propagation algorithmic learning. …”
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  15. 15
    Suspicious activity trigger system using YOLOv6 convolutional neural network

    Suspicious activity trigger system using YOLOv6 convolutional neural network by Suryanti, Awang, Mohd Qhairel, Rafiqi Rokei, Sulaiman, Junaida

    Published 2023
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  16. 16
    Software agent as an effective tool for managing the Internet of thing data complexity

    Software agent as an effective tool for managing the Internet of thing data complexity by Mustafa, M.B., Yusoof, M.A.M.

    Published 2017
    “…On top of that software agent-based approach to big data management in IoT consider resource-constrained devices, allowing better resource management. The use of software-agent based middleware that is intelligent, enables the system to adapt to the ever changing in taste and preferences of users when predicting the buying intention, thus making the online marketing to be highly effective. …”
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  17. 17
    Adaptive approach in handling human inactivity in computer power management

    Adaptive approach in handling human inactivity in computer power management by Candrawati, Ria, Hashim, Nor Laily

    Published 2016
    “…This study introduces Control, Learn and Knowledge model that adapts the Monitor, Analyze, Planning, Execute control loop integrates with Q Learning algorithm to learn human inactivity period to minimize the computer power consumption.An experiment to evaluate this model was conducted using three case studies with same activities. …”
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  18. 18
    Digital Transformation Using Industry 4.0 and Artificial Intelligence

    Digital Transformation Using Industry 4.0 and Artificial Intelligence by Keerthika M., Pragadeesh M., Santhiya M., Jebamalar G.B., Venu H.

    Published 2025
    “…Explainable artificial intelligence (XAI) conducts studies and creates tools, techniques, and algorithm designs that produce information and judgments made by AI-based systems that are comprehensible to humans. …”
    Book chapter
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  19. 19
    Evolution of AI enabled healthcare systems using textual data with a pretrained BERT deep learning model

    Evolution of AI enabled healthcare systems using textual data with a pretrained BERT deep learning model by Wang, Yi Jie, Choo, Wei Chong, Ng, Keng Yap, Bi, Ran, Wang, Peng Wei

    Published 2025
    “…The overall goal is to uncover emerging trends and potential future paths of AI in healthcare by applying text mining to collect scientific papers and patent information. This study, using advanced text mining and multiple deep learning algorithms, utilized the Web of Science for scientific papers (1587) and the Derwent innovations index for patents (1314) from 2018 to 2022 to study future trends of emerging AI in healthcare. …”
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  20. 20
    Simulink Implementation of Digital Cascade Control DC Motor Model - A didactic approach

    Simulink Implementation of Digital Cascade Control DC Motor Model - A didactic approach by Kamarudin, Muhammad Nizam, Md Rozali, Sahazati

    Published 2008
    “…Various control method shown in this paper provides interactive learning on how to perform conventional proportional – integral (PI) controller and intelligent self tuning PI controller using fuzzy algorithm. …”
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