Search Results - (( intelligence system _ algorithm ) OR ( intelligence self learning algorithm ))
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1
Intelligent agent for e-commerce using genetic algorithm / 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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Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof
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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Advancements and challenges in mobile robot navigation: a comprehensive review of algorithms and potential for self-learning approaches
Published 2024“…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.]
Published 2023“…It is based on the use of sensors, actuators, sophisticated algorithms, machine learning systems, and robust processors. …”
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An intelligent framework for modelling and active vibration control of flexible structures
Published 2004“…Parametric and non-parametric modelling of such systems is investigated. Parametric approaches include linear parametric modelling of the system using recursive least squares (RLS) and genetic algorithms (GAS); and non-parametric approaches include multi-layered perceptron neural networks (MLP-NNs) and adaptive neuro-fuzzy inference systems (ANFIS) are employed. …”
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6
Lithium-ion Battery State of Charge Estimation Method Using Optimized Deep Recurrent Neural Network Algorithm
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…”
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Machine learning: tasks, modern day applications and challenges
Published 2019“…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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A Survey of Stochastic processes in Wireless Sensor Network: a Power Management Prospective
Published 2013“…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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9
Nature-Inspired cognitive evolution to play Ms. Pac-Man
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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A pond-surface-based Biofloc-farm health-monitoring system for African catfish using deep learning methods
Published 2022“…The expected outcome of this is an artificial intelligence system that can determine the well-being of the fishes in a Biofloc pond based on the behaviour of the fish that can be observed from the simulated environment of the pond. …”
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The development of a tracking algorithm for ambulance detection using squaring of RGB and HSV color processing techniques
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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12
Teaching and learning via chatbots with immersive and machine learning capabilities
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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Review of intelligence for additive and subtractive manufacturing: current status and future prospects
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. Challenges in implementing intelligent additive and subtractive manufacturing systems are also discussed in the article. …”
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Utilisation of Exponential-Based Resource Allocation and Competition in Artificial Immune Recognition System
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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15
An improved negative selection algorithm based on the hybridization of cuckoo search and differential evolution for anomaly detection
Published 2018“…The V-Detectors algorithm depends greatly on the random detectors generated in monitoring the status of a system. …”
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16
Neuro Symbolic Integration and Agent Based Modelling
Published 2018“…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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Permodelan Rangkaian Neural Buatan Untuk Penilaian Kendiri Teknologi Maklumat Guru Pelatih
Published 2001“…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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19
Software agent as an effective tool for managing the Internet of thing data complexity
Published 2017“…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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Adaptive approach in handling human inactivity in computer power management
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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