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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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Graph-Based Algorithm With Self-Weighted And Adaptive Neighbours Learning For Multi-View Clustering by He, Yanfang

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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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An improved pheromone-based kohonen self-organising map in clustering and visualising balanced and imbalanced datasets by Azlin, Ahmad, Rubiyah, Yusof, Nor Saradatul Akmar, Zulkifli, Mohd Najib, Ismail

“…However, similar to other clustering algorithms, this algorithm requires sufficient data for its unsupervised learning process. …”
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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.

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

“…Machine Learning is concerned in constructing models which can learn and make predictions based on data. …”
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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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An Improved Pheromone-Based Kohonen Self- Organising Map in Clustering and Visualising Balanced and Imbalanced Datasets by Ahmad, Azlin, Yusof, Rubiyah, Zulkifli, Nor Saradatul Akma, Ismail, Mohd Najib

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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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BIOLOGICAL INSPIRED INTRUSION PREVENTION AND SELF-HEALING SYSTEM FOR CRITICAL SERVICES NETWORK by MOHAMED AHMED ELSHEIK, MUNA ELSADIG

“…Secondly, specification language, system design, mathematical and computational models for IPS and SH system are established, which are based upon nonlinear classification, prevention predictability trust, analysis, self-adaptation and self-healing algorithms. …”
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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.

Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets by Saeed, Sana

“…A new self-adaptive hybrid algorithm (CSCMAES) is introduced for optimization. …”
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Imitation learning through self-exploration : from body-babbling to visuomotor association / Farhan Dawood by Dawood, Farhan

“…The results show that the imitation learning algorithm is able to incrementally learn and associate the observed motion patterns based on the segmentation of motion primitives.…”
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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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Self-organizing network technique for resource allocation and mobility management in LTE femtocell network / Labeeb Mohsin Abdullah by Abdullah, Labeeb Mohsin

“…In this thesis, the issues of concern include assigning the limited resources of Physical Cell Identity (PCI) for the high number of deployed femtocells, to ensure network collision and confusion free after deploying the PCI, determine the exact geographic location of femtocell, and identifying the learning parameters for the optimized self—organizing handover process for LTE femtocell-based networks. …”
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Quantum-Inspired Multidirectional Associative Memory With a Self-Convergent Iterative Learning by Masuyama, Naoki, Loo, Chu Kiong, Seera, Manjeevan, Kubota, Naoyuki

“…We introduce a quantum-inspired multidirectional associative memory (QMAM) with a one-shot learning model, and QMAM with a self-convergent iterative learning model (IQMAM) based on QHAM in this paper. …”
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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

“…This study aimed to determine the spatiotemporal pattern of the water quality data and identifying the sources of pollution in the Klang River Basin. The self organizing map (SOM) combined with the K-means algorithm arranged the data based on the relationships of 25 variables. …”
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Topological Clustering via Adaptive Resonance Theory With Information Theoretic Learning by Masuyama, Naoki, Loo, Chu Kiong, Ishibuchi, Hisao, Kubota, Naoyuki, Nojima, Yusuke, Liu, Yiping

“…Other types of the ART-based topological clustering algorithms have been developed, however, these algorithms have various drawbacks such as a large number of parameters, sensitivity to noisy data. …”
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