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

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

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

“…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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Advancements and challenges in mobile robot navigation: a comprehensive review of algorithms and potential for self-learning approaches by Al Mahmud, Suaib, Kamarulariffin, Abdurrahman, Mohd Ibrahim, Azhar, Haja Mohideen, Ahmad Jazlan

“…With the goal of enhancing the autonomy in mobile robot navigation, numerous algorithms (traditional AI-based, swarm intelligence-based, self-learning-based) have been built and implemented independently, and also in blended manners. …”
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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

“…It is based on the use of sensors, actuators, sophisticated algorithms, machine learning systems, and robust processors. …”
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Machine learning: tasks, modern day applications and challenges by Aljuaid, Lamyaa Zaed, Koh, Tieng Wei, Sharif, Khaironi Yatim

“…Machine learning algorithms learned from available data. Further, this learning laid the foundation to develop AI for the various systems around us. …”
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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.

“…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…”

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

“…The simulation algorithm and interactive environment thus developed and validated form suitable test and verification platforms for the development of AVC strategies for flexible structures as well as for learning and research purposes.…”
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Teaching and learning via chatbots with immersive and machine learning capabilities by Nantha Kumar Subramaniam

“…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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A Survey of Stochastic processes in Wireless Sensor Network: a Power Management Prospective by Ul haq, Riaz, Norrozila, Sulaiman, Muhammad, Alam

“…Statistical tools are quite famous for the decision making procedure in artificial intelligence, self-learning and neural network. A huge research has been done in the recent era on power management and energy efficient protocols to improve the efficiency of the WSN. …”
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A pond-surface-based Biofloc-farm health-monitoring system for African catfish using deep learning methods by Nizam Nordin

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

“…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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Neuro Symbolic Integration and Agent Based Modelling by Sathasivam , Saratha, Velavan, Muraly

“…Logic program and neural networks are two important perspectives in artificial intelligence. The major domain of neuro-symbolic integration is designed by the theory are usually known as deductive systems which less such elements of human reasoning as adaptation, learning and self-organisation. …”
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The development of a tracking algorithm for ambulance detection using squaring of RGB and HSV color processing techniques by Mohammad Syawaludin Syafiq, Hassan

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

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

“…Next, the Real World Tournament Selection method is adapted and incorporated into the resource competition of Artificial Immune Recognition System. The proposed algorithms have been tested on a variety of datasets from the UCI machine learning repository. …”
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An improved negative selection algorithm based on the hybridization of cuckoo search and differential evolution for anomaly detection by Ayodele Nojeem, Lasisi

“…The V-Detectors algorithm depends greatly on the random detectors generated in monitoring the status of a system. …”
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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

“…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. Challenges in implementing intelligent additive and subtractive manufacturing systems are also discussed in the article. …”
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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

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

“…The research procedures chosen were the multi-layered perceptron with back propagation algorithmic learning. The research findings show that the most suitable predictive model comprises of eleven nodes in input-layer; five nodes in hidden-layer and one node in output-layer. …”
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Digital Transformation Using Industry 4.0 and Artificial Intelligence by Keerthika M., Pragadeesh M., Santhiya M., Jebamalar G.B., Venu H.

“…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. …”