Search Results - (( intelligence mobile learning algorithm ) OR ( intelligence system bas algorithm ))

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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Adaptive route optimization for mobile robot navigation using evolutionary algorithm by Kit Guan Lim, Guan Lim, Yoong Hean Lee, Hean Lee, Min Keng Tan, Keng Tan, Hou, Pin Yoong, Tienlei, Wang, Tze, Kenneth Kin Teo

“…As technologies are advancing, demand for an intelligent mobile robot also increases. In autonomous robot design, the main problem faced by researchers is the path planning of mobile robot. …”
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A Modified Hybrid Fuzzy Controller for Real-Time Mobile Robot Navigation by Hossen J., Sayeed S., Iqbal A.K.M.P.

“…Algorithms; Controllers; Fuzzy clustering; Fuzzy systems; Intelligent control; Intelligent systems; Learning algorithms; Least squares approximations; Membership functions; Mobile robots; Navigation; Robotics; Robots; Smart sensors; and ANFIS; Apriori algorithms; Fuzzy C mean; Gradient descent algorithms; Hybrid-fuzzy controllers; Mobile Robot Navigation; Subtractive clustering; Subtractive clustering algorithms; Clustering algorithms…”

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

“…These proves that without prior knowledge, the hybrid AI algorithm can self-learn. In the future the research on improving the algorithm learning will be studied and the implementation in other types of autonomous system other mobile robot obstacle avoidance will be considered.…”
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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

“…Purpose – Prediction accuracies are usually affected by the techniques and devices used as well as the algorithms applied. 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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Artificial Intelligence Integration in Mobile Applications: Innovation and Challenges in Supporting Quran Memorization and Review by Khairulnazrin Nasir, Rahim Kamarul Zaman, Ahmad Bazli Ahmad Hilmi, Abdul Hakim Mahadzir, Ahmad Mukhlis bin Mustaffa

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

“…Purpose – Prediction accuracies are usually affected by the techniques and devices used as well as the algorithms applied. 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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Insomnia audio therapy mobile application with music recommender system / Nur Azmina Mohamad Zamani, Nasiroh Omar and Nur Damira Huda Azmi by Mohamad Zamani, Nur Azmina, Omar, Nasiroh, Azmi, Nur Damira Huda

“…The proposed mobile application with machine learning music recommender system will provide a basis for the realization of intelligent music therapy in treating insomnia disorder patients as well as in other music applications.…”
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A new mobile botnet classification based on permission and API calls by Yusof M., Madihah Mohd Saudi, Farida Hazwani Mohd Ridzuan

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Multi-Agent Reinforcement Learning For Swarm Robots Formation by Bujang, Christina

“…The reinforcement learning algorithm offers one of the most general frameworks in learning subjects to address some of the control issues in a multi-agent system. …”
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Optimize and deploy machine learning algorithms on embedded devices for manufacturing applications by Teoh, Ming Xue

“…In recent studies, we seen developers and researchers proposing solutions on deep learning algorithms like YOLO, EfficientNet, CNN, MobileNet etc. …”
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Artificial intelligent power prediction for efficient resource management of WCDMA mobile network by Tee Y.K., Tinng S.K., Koh J., David Y.

“…This artificial intelligent call admission control (CAC) was validated using a dynamic WCDMA mobile network simulator. …”

Designing machine learning frameworks for intelligence and gamification research / Nordin Abu Bakar by Abu Bakar, Nordin

“…Machine learning frameworks have been utilised to facilitate intelligence as operational mechanism in intelligence embedded system such as learning system, prediction protocol and robot navigation system. …”
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Android malware detection using PMCC heatmap and Fuzzy Unordered Rule Induction Algorithm (FURIA) by Nur Khairani, Kamarudin, Ahmad Firdaus, Zainal Abidin, Azlee, Zabidi, Ferda, Ernawan, Syifak, Izhar Hisham, Mohd Faizal, Ab Razak

“…However, in machine learning intelligence detection, too many insignificant features will decrease the percentage of the detection’s accuracy. …”
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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

“…The self-driving car is a type of autonomous vehicle that can drive autonomously based on Artificial Intelligence (AI). It is based on the use of sensors, actuators, sophisticated algorithms, machine learning systems, and robust processors. …”
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Empirical study on intelligent android malware detection based on supervised machine learning by Abdullah, Talal A.A., Ali, Waleed, Abdulghafor, Rawad Abdulkhaleq Abdulmolla

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Light weight deep learning algorithm for voice call quality of services (Qos) in cellular communication by Ramalingam, Mritha, Sultanuddin, S. J., Nithya, N., Raj, T. F. Michael, Kumar, T. Rajesh, Prasad, S. J. Suji, Al-Ammar, Essam A., Siddique, M. H., Udayakumar, Sridhar

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A Mobile App to Predict Disease Based on Symptoms Using Artificial Intelligence by H’ng, Sheng Wei

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Tag cloud algorithm with the inclusion of personality traits by Supli, Ahmad Affandi, Shiratuddin, Norshuhada, Ab. Aziz, Azizi

“…Therefore, the main objective of this study is to make tag cloud algorithm with the inclusion of personality traits by adjusting two prominent visual features (color and shape) as an integration of layout.In addition, the utilization of RBS (rule bas e system) approach as artificial intelligent method is also taken into account to make knowledge base that stores the relationship between the proper personality elements and particular layout.This paper also discusses findings from satisfaction evaluation of prototyping, which comprises three dimensions facet: overall layout, color, and shape .The findings showed that the majority mean value for each dimension is categorized in agree scale (6-point), which indicates that respondents are satisfied with the tag cloud layout display generated by proposed algorithm.The findings suggest interface designers to be careful in selecting the appropriate tag clouds layout to be displayed for users with varying personality differences.…”
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Usability prioritization using performance metrics and hierarchical agglomerative clustering in MAR-learning application by Cheng L.K., Selamat A., Mohamed Zabil M.H., Selamat M.H., Alias R.A., Puteh F., Mohamed F., Krejcar O.

“…Artificial intelligence; Augmented reality; Cluster analysis; Computer aided instruction; Learning systems; Usability engineering; Agglomerative clustering; English language teaching; Mobile augmented reality; Unsupervised machine learning; Usability; Learning algorithms…”