Search Results - (( java implementation bat algorithm ) OR ( using self learning algorithm ))

Fuzzy modeling using Bat Algorithm optimization for classification by Noor Amidah, Ahmad Sultan

“…A Sazonov Engine which is a fuzzy java engine is use to apply Bat Algorithm in the experiment. …”
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Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof by Yusof, Yusman

“…From the reviews, it is evident that autonomous system is set to handle finite number of encountered states using finite sequences of actions. In order to learn the optimized states-action policy the self-learning algorithm is developed using hybrid AI algorithm by combining unsupervised weightless neural network, which employs AUTOWiSARD and reinforcement learning algorithm, which employs Q-learning. …”
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Graph-Based Algorithm With Self-Weighted And Adaptive Neighbours Learning For Multi-View Clustering by He, Yanfang

“…To address this issue, this study incorporated joint graph learning from the gmc algorithm into swmcan, creating a new algorithm called swmcan-jg. …”
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Contrastive Self-Supervised Learning for Image Classification by Tan, Yong Le

“…Thus, people have introduced a new paradigm that falls under unsupervised learning – self-supervised learning. Through self-supervised learning, pretraining of the model can be conducted without any human-labelled data and the model can learn from the data itself. …”
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Development of web based learning content of animation algorithm on searching and sorting techniques / Nur Linda Abdi Nur by Abdi Nur, Nur Linda

“…The objectives of this project is to develop self-learning environment in learning searching and sorting algorithm, enhance understanding of student in learning searching and sorting technique and to apply web-based learning in computer science subject, which focus on courses that use searching and sorting algorithm.…”
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Activity recognition using one-versus-all strategy with relief-f and self-adaptive algorithm by Zainudin, Muhammad Noorazlan Shah, Sulaiman, Md. Nasir, Mustapha, Norwati, Perumal, Thinagaran

“…Many researchers dealing with smartphone sensors to recognize human activities using machine learning algorithms. In this paper, we proposed One-versus-All (OVA) strategy with relief-f and self-adaptive algorithm to recognize these activities. …”
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The use of SOM for fingerprint classification by Turky A.M., Ahmad M.S.

“…This paper introduces an approach to fingerprint classification by using Self-Organizing Maps (SOM). In order to be able to deal with fingerprint images having distorted regions, the SOM learning and classification algorithms are modified. …”

A comparative sales forecast study between supervised and unsupervised learning algorithm on restaurant / Azhar Tamby by Tamby, Azhar

“…In this research, there are two algorithm of neural network will be used. It is coming from supervised and unsupervised learning algorithm. …”
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Feasibility comparison of HAC algorithm on usability performance and self-reported metric features for MAR learning by Cheng L.K., Selamat A., Zabil M.H.M., Selamat M.H., Alias R.A., Puteh F., Mohamed F., Krejcar O., Herrera-Viedma E., Fujita H.

Novel direct and self-regulating approaches to determine optimum growing multi-experts network structure by Loo, C.K., Rajeswari, M., Rao, M.V.C.

“…SGMN adopts self-adaptive learning rates for gradient-descent learning rules. …”
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An improved self organizing map using jaccard new measure for textual bugs data clustering by Ahmed, Attika

“…Considering the unsupervised learning algorithms, Self-Organizing Map (SOM) considers the equally compatible algorithm for clustering, as both algorithms are closely related but different in way they were used in data mining. …”
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An improved self organizing map using jaccard new measure for textual bugs data clustering by Ahmed, Attika

“…Considering the unsupervised learning algorithms, Self­Organizing Map (SOM) considers the equally compatible algorithm for clustering, as both algorithms are closely related but different in way they were used in data mining. …”
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BIOLOGICAL INSPIRED INTRUSION PREVENTION AND SELF-HEALING SYSTEM FOR CRITICAL SERVICES NETWORK by MOHAMED AHMED ELSHEIK, MUNA ELSADIG

“…Using the software system, design theories, AIS features, new nonlinear classification algorithm, and self-healing system show how the use of presented systems can ensure safety for critical services networks and heal the damage caused by intrusion. …”
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Suicide and self-harm prediction based on social media data using machine learning algorithms by Abdulrazak Yahya, Saleh, Fadzlyn Nasrini, Mostapa

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Self learning neuro-fuzzy modeling using hybrid genetic probabilistic approach for engine air/fuel ratio prediction by Al-Himyari, Bayadir Abbas

“…This work facilitates in achieving a self-generating FRBS from real data. The GA-FBC can be used as a new direction in machine learning research. …”
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Optimisation of fed-batch fermentation process using deep reinforcement learning by Chai, Wan Ying

“…Fed-batch fermentation process has always been a challenge for optimisation because it is highly non-linear and complex. Deep reinforcement learning is a self-learning algorithm through trial and error and experience, without any prior knowledge. …”
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Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

“…Therefore, feature selection using Relief-f with self-adaptive Differential Evolution (rsaDE) algorithm is proposed to select the most significant features. …”
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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.

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

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Autism spectrum self-stimulatory behaviours classification using explainable temporal coherency deep networks and SVM classifier / Liang Shuaibing by Liang , Shuaibing

“…Doctors require years of clinical training to acquire the ability to capture these behavioural cues such as self–stimulatory behaviours. In recent years, the advancement of deep learning algorithms and hardware enabled the use of artificial intelligence technology to automatically capture self-stimulatory behaviours. …”
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