Search Results - (("pattern machine algorithm") OR ((("new learning algorithm") OR ("self learning algorithm"))))

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

“…In this thesis the research of a self-learning algorithm will be presented, outlined and discussed in detailed manner. …”
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Education in the Era of IR 4.0 by Hasnah, Haron

“…IR 4.0 also known as the ‘digital revolution’: combines technological and human capacities in an unprecedented way through self- learning algorithms, self-driving cars, human–machine interconnection and big-data analytics.…”
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New learning algorithm based on Hidden Markov Model (HMM) as stochastic modelling for pattern calssification by Balakrishnan, Malarvili, Ting, Chee Ming, Shaikh Salleh, Sheikh Hussain

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Two-wheel balancing robot; review on control methods and experiments by Mohd Romlay, Mohamad Rabani, Mohd. Ibrahim, Azhar, Toha, Siti Fauziah, Rashid, Muhammad Mahbubur

“…This article intended to address the control methods of balancing two-wheeled mobile robot from linear controller, non-linear controller and adapting and self-learning algorithm. The focus of the review will be the evaluation and experiment done on two-wheel mobile robot. …”
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One day ahead daily peak hour load forecasting by using invasive weed optimization learning algorithm based Artificial Neural Network by Rahim, Muhammad Fitri

“…Hence, this indicates that Invasive Weed Optimization could be implemented as a new learning algorithm for an Artificial Neural Network.…”
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Chaos search in fourire amplitude sensitivity test by Koda, Masato

“…This paper explores the characterization of learning functions involved in FAST and derives the underlying dynamical relationships with chaos search, which can provide new learning algorithms. This contribution has proven the general link that exists between chaos search and FAST, which helps us exploit the ergodicity of chaos search in AI applications.…”
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Chaos Search in Fourier Amplitude Sensitivity Test by Koda, Masato

“…This paper explores the characterization of learning functions involved in FAST and derives the underlying dynamical relationships with chaos search, which can provide new learning algorithms. This contribution has proven the general link that exists between chaos search and FAST, which helps us exploit the ergodicity of chaos search in AI applications.…”
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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

“…The findings suggest that, even though the self-learning algorithms require huge amounts of training data and have the possibility of learning erroneous behavior, they possess huge potential to overcome challenges rarely addressed by the other traditional algorithms. …”
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Optimisation of fed-batch fermentation process using deep reinforcement learning by Chai, Wan Ying

“…Deep reinforcement learning is a self-learning algorithm through trial and error and experience, without any prior knowledge. …”
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Ensemble Dual Algorithm Using RBF Recursive Learning for Partial Linear Network by Md Akib, Afif, Saad, Nordin, Asirvadam, Vijanth

“…Radial basis function (RBF) is used to define the non-linear weight of the partial linear network. A new learning algorithm called the ensemble dual algorithm for estimating the mass-flow rate of the flow after leakage is proposed. …”
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Extreme learning machine for user location prediction in mobile environment by Mantoro, Teddy, Olowolayemo, Akeem, Olatunji, Sunday O., Ayu, Media Anugerah, Md. Tap, Abu Osman

“…This work aims to attempt to further devise a better positioning accuracy based on location fingerprinting taking advantage of two important mobile fingerprints, namely signal strength (SS) and signal quality (SQ) and subsequently building a model based on extreme learning machine (ELM), a new learning algorithm for single-hidden-layer neural networks. …”
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Extreme learning machine for user location prediction in mobile environment by Mantoro, Teddy, Olowolayemo, Akeem, Olatunji, Sunday O., Ayu, Media A., Abu Osman, Md. Tap

“…This work aims to attempt to further devise a better positioning accuracy based on location fingerprinting taking advantage of two important mobile fingerprints, namely signal strength (SS) and signal quality (SQ) and subsequently building a model based on extreme learning machine (ELM), a new learning algorithm for single-hidden-layer neural networks. …”
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Enhancing the QoS performance for mobile station over LTE and WiMAX networks / Mhd Nour Hindia by Hindia, Mhd Nour

“…The selection is based on the user preferences since it uses a self-learning algorithm to determine triggers and handover thresholds dynamically. …”
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