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Journal articles on the topic 'Intelligent and adaptive learning systems'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

Phobun, Pipatsarun, and Jiracha Vicheanpanya. "Adaptive intelligent tutoring systems for e-learning systems." Procedia - Social and Behavioral Sciences 2, no. 2 (2010): 4064–69. http://dx.doi.org/10.1016/j.sbspro.2010.03.641.

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Kasabov, Nikola, and Robert Kozma. "Self-Organization and Adaptation in Intelligent Systems." Journal of Advanced Computational Intelligence and Intelligent Informatics 2, no. 6 (1998): 177. http://dx.doi.org/10.20965/jaciii.1998.p0177.

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This special issue is devoted to one of the important topics of current intelligent information systems-their ability to adapt to the environment they operate in, as adaptation is one of the most important features of intelligence. Several milestones in the literature on adaptive systems mark the development in this area. The Hebbian learning rule,1) self-organizing maps,2,3) and adaptive resonance theory4) have influenced the research in this area a great deal. Some current development suggests methods for building adaptive neurofuzzy systems,5) and adaptive self-organizing systems based on p

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Hafidi, Mohamed, and Tahar Bensebaa. "Developing Adaptive and Intelligent Tutoring Systems (AITS)." International Journal of Information and Communication Technology Education 10, no. 4 (2014): 70–85. http://dx.doi.org/10.4018/ijicte.2014100106.

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Several adaptive and intelligent tutoring systems (AITS) have been developed with different variables. These variables were the cognitive traits, cognitive styles, and learning behavior. However, these systems neglect the importance of learner's multiple intelligences, learner's skill level and learner's feedback when implementing personalized mechanisms. In this paper, the authors propose AITS based not only on the learner's multiple intelligences, but also the changing learning performance of the individual learner during the learning process. Therefore, considering learner's skill level and

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Kivuva, Faith Ngami, Elizaphan Maina, and Rhoda Gitonga. "Multi-Agent Adaptive e-Learning System Based on Learning Styles." Open Journal for Information Technology 4, no. 1 (2021): 1–12. http://dx.doi.org/10.32591/coas.ojit.0401.01001k.

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Most traditional e-learning system fails to provide the intelligence that a learner may require during their learning process. Different learners have different learning styles but the current e-learning systems are not able to provide personalized learning. In this paper, we discuss how intelligent agents can aid learners in their learning process. Three agents have been developed namely, learner agent, information agent, and tutor agents that will be integrated into a learning management system (Moodle). Learners are provided with a personalized recommendation based on the learning styles.

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Schull, Jonathan. "Are species intelligent?" Behavioral and Brain Sciences 13, no. 1 (1990): 63–75. http://dx.doi.org/10.1017/s0140525x00077542.

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AbstractPlant and animal species are information-processing entities of such complexity, integration, and adaptive competence that it may be scientifically fruitful to consider them intelligent. The possibility arises from the analogy between learning (in organisms) and evolution (in species), and from recent developments in evolutionary science, psychology and cognitive science. Species are now described as spatiotemporally localized individuals in an expanded hierarchy of biological entities. Intentional and cognitive abilities are now ascribed to animal, human, and artificial intelligence s

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Choi, Younyoung, and Cayce McClenen. "Development of Adaptive Formative Assessment System Using Computerized Adaptive Testing and Dynamic Bayesian Networks." Applied Sciences 10, no. 22 (2020): 8196. http://dx.doi.org/10.3390/app10228196.

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Online formative assessments in e-learning systems are increasingly of interest in the field of education. While substantial research into the model and item design aspects of formative assessment has been conducted, few software systems embodied with a psychometric model have been proposed to allow us to adaptively implement formative assessments. This study aimed to develop an adaptive formative assessment system, called computerized formative adaptive testing (CAFT) by using artificial intelligence methods based on computerized adaptive testing (CAT) and Bayesian networks as learning analyt

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ZHANG, YUMING, QIYUE WANG, and YUKANG LIU. "Adaptive Intelligent Welding Manufacturing." Welding Journal 100, no. 01 (2021): 63–83. http://dx.doi.org/10.29391/2021.100.006.

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Optimal design of the welding procedure gives the desired welding results under nominal welding conditions. During manufacturing, where the actual welding manufacturing conditions often deviate from the nominal ones used in the design, applying the designed procedure will produce welding results that are different from the desired ones. Adaption is needed to make corrections and adjust some of the welding parameters from those specified in the design. This is adaptive welding. While human welders can be adaptive to make corrections and adjustments, their performance is limited by their physica

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Bimba, Andrew Thomas, Norisma Idris, Ahmed Al-Hunaiyyan, Rohana Binti Mahmud, and Nor Liyana Bt Mohd Shuib. "Adaptive feedback in computer-based learning environments: a review." Adaptive Behavior 25, no. 5 (2017): 217–34. http://dx.doi.org/10.1177/1059712317727590.

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Adaptive support within a learning environment is useful because most learners have different personal characteristics such as prior knowledge, learning progress, and learning preferences. This study reviews various implementation of adaptive feedback, based on the four adaptation characteristics: means, target, goal, and strategy. This review focuses on 20 different implementations of feedback in a computer-based learning environment, ranging from multimedia web-based intelligent tutoring systems, dialog-based intelligent tutoring systems, web-based intelligent e-learning systems, adaptive hy

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Tsortanidou, Xanthippi, Charalampos Karagiannidis, and Adamantios Koumpis. "Adaptive Educational Hypermedia Systems based on Learning Styles: the Case of Adaptation Rules." International Journal of Emerging Technologies in Learning (iJET) 12, no. 05 (2017): 150. http://dx.doi.org/10.3991/ijet.v12i05.6967.

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This paper investigates the pedagogical basis of Adaptive Educational Hypermedia Systems (AEHS) that incorporate Learning Styles in order to accommodate user's learning style preferences and needs. Therefore, AES adapt the learning content, its presentation and navigation to the user's learning style preferences. We collect thirty three (33) Adaptive and Intelligent Web-based Educational Systems (AIWBES) that incorporate learning styles and discuss twenty of them, namely the AEHS, as the remaining are Intelligent Tutorng Systems. The main achievement of this work is the investigation of AEHS'

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Angelides, Marios C., and Amelia K. Y. Tong. "Implementing Multiple Tutoring Strategies in an Intelligent Tutoring System for Music Learning." Journal of Information Technology 10, no. 1 (1995): 52–62. http://dx.doi.org/10.1177/026839629501000107.

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Variation in tutoring strategies plays an important part in intelligent tutoring systems. The potential for providing an adaptive intelligent tutoring system depends on having a range of tutoring strategies to select from. In order to react effectively to the student's needs, an intelligent tutoring system has to be able to choose intelligently among the strategies and determine which strategy is best for an individual student at a particular moment. This paper describes, through the discussion pertaining to the implementation of SONATA, a music theory tutoring system, how an intelligent tutor

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Juuso, Esko K. "Smart Adaptive Big Data Analysis with Advanced Deep Learning." Open Engineering 8, no. 1 (2018): 403–16. http://dx.doi.org/10.1515/eng-2018-0043.

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Abstract Increasing volumes of data, referred as big data, require massive scale and complex computing. Artificial intelligence, deep learning, internet of things and cloud computing are proposed for heterogeneous datasets in hierarchical analytics to manage with the volume, variety, velocity and value of the big data. These solutions are not sufficient in technical systems where measurements, waveform signals, spectral data, images and sparse performance indicators require specific methods for the feature extraction before interactions can be properly analysed. In practical applications, the

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MEHRABIAN, ALI REZA, and CARO LUCAS. "INTELLIGENT ADAPTIVE CONTROL OF NON-LINEAR SYSTEMS BASED ON EMOTIONAL LEARNING APPROACH." International Journal on Artificial Intelligence Tools 16, no. 01 (2007): 69–85. http://dx.doi.org/10.1142/s0218213007003205.

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Drawing upon the past research on neuromorphic implementation of an emotionally intelligent control system, a developed version of the brain emotional learning based intelligent controller, BELBIC, is proposed in this paper. The modified system, which essentially realizes direct adaptive control scheme, deals very well for SISO plants, and does not need any pre-training. It is adaptive and robust with respect to changes in the environment since it learns to produce appropriate control actions on-line. An additional advantage of BELBIC is its simplicity as well as low computational load. The pe

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Bin Rodzman, Shaiful Bakhtiar, Nordin Abu Bakar, Yun-Huoy Choo, et al. "I-OnAR: a rule-based machine learning approach for intelligent assessment in an online learning environment." Indonesian Journal of Electrical Engineering and Computer Science 17, no. 2 (2020): 1021. http://dx.doi.org/10.11591/ijeecs.v17.i2.pp1021-1028.

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Intelligent systems are created to automate decision making process that is similar to human intelligence. Incorporating intelligent component has achieved promising results in many applications, including in education. Intelligence modules in a tutoring system would bring the application and its capability closer to a human's ability to serve its human users and to solve problems. However, the majority of the online learning provided in the literature review especially in Malaysia, normally only provide the lecture notes, assignments and tests and rarely suggest or give feedbacks on what the

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Iglesias, Ana, Paloma Martínez, Ricardo Aler, and Fernando Fernández. "Reinforcement learning of pedagogical policies in adaptive and intelligent educational systems." Knowledge-Based Systems 22, no. 4 (2009): 266–70. http://dx.doi.org/10.1016/j.knosys.2009.01.007.

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Beyyoudh, Mohammed, Mohammed Khalidi Idrissi, and Samir Bennani. "Towards a New Generation of Intelligent Tutoring Systems." International Journal of Emerging Technologies in Learning (iJET) 14, no. 14 (2019): 105. http://dx.doi.org/10.3991/ijet.v14i14.10664.

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In this paper, a new approach of intelligent tutoring systems based on adaptive workflows and serious games is proposed. The objective is to use workflows for learning and evaluation process in the activity-based learning context. We aim to implement a system that allow the coexistence of an intelligent tutor and a human tutor who could control and follow-up the execution of the learning processes and intervene in blocking situations. Serious games will be the pillar of the evalu-ation process. The purpose is to provide new summative evaluation methods that increase learner’s motivation and en

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Colchester, Khalid, Hani Hagras, Daniyal Alghazzawi, and Ghadah Aldabbagh. "A Survey of Artificial Intelligence Techniques Employed for Adaptive Educational Systems within E-Learning Platforms." Journal of Artificial Intelligence and Soft Computing Research 7, no. 1 (2017): 47–64. http://dx.doi.org/10.1515/jaiscr-2017-0004.

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Abstract The adaptive educational systems within e-learning platforms are built in response to the fact that the learning process is different for each and every learner. In order to provide adaptive e-learning services and study materials that are tailor-made for adaptive learning, this type of educational approach seeks to combine the ability to comprehend and detect a person’s specific needs in the context of learning with the expertise required to use appropriate learning pedagogy and enhance the learning process. Thus, it is critical to create accurate student profiles and models based up

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Popova, Y. B. "From LMS to adaptive training systems." «System analysis and applied information science», no. 2 (August 28, 2019): 58–64. http://dx.doi.org/10.21122/2309-4923-2019-2-58-64.

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The use of information technology and, in particular, learning management systems, increases the ability of both the teacher and the learner to achieve their goals in the educational process. Such systems provide educational content, help organize and monitor training, collect progress statistics, and can also take into account the individual characteristics of each user of the system. The purpose of this study is to determine the direction of development of modern learning systems and technologies for their implementation. The evolution of learning management systems, the transition to intell

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Hou, Ming, and Cali Fidopiastis. "A generic framework of intelligent adaptive learning systems: from learning effectiveness to training transfer." Theoretical Issues in Ergonomics Science 18, no. 2 (2016): 167–83. http://dx.doi.org/10.1080/1463922x.2016.1166405.

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BONTCHEVA, KALINA, and VANIA DIMITROVA. "EXAMINING THE USE OF CONCEPTUAL GRAPHS IN ADAPTIVE WEB-BASED SYSTEMS THAT AID TERMINOLOGY LEARNING." International Journal on Artificial Intelligence Tools 13, no. 02 (2004): 299–331. http://dx.doi.org/10.1142/s0218213004001569.

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This paper discussed the use of Conceptual Graphs (CGs) for implementing tasks employed in web-based educational systems that aid terminology learning. Specifically, we focus on two critical issues in intelligent tutoring - student diagnosis and generation of adaptive explanations. Both tasks are demonstrated in terminological domains where learners have to familiarize themselves with concepts in a specific subject area (e.g. computing, finance, chemistry). Based on CG reasoning, robust and computationally tractable algorithms for student modelling and adaptive explanation generation are defin

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Shervais, S., T. T. Shannon, and G. G. Lendaris. "Intelligent supply chain management using adaptive critic learning." IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans 33, no. 2 (2003): 235–44. http://dx.doi.org/10.1109/tsmca.2003.809214.

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Nabeth, Thierry, Liana Razmerita, Albert Angehrn, and Claudia Roda. "INCA: A cognitive multi-agents architecture for designing intelligent & adaptive learning systems." Computer Science and Information Systems 2, no. 2 (2005): 99–114. http://dx.doi.org/10.2298/csis0502099n.

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This paper presents a cognitive multi-agents architecture called Intelligent Cognitive Agents (InCA) that was elaborated for the design of Intelligent Adaptive Learning Systems. The InCA architecture relies on a personal agent that is aware of the user's characteristics, and that coordinates the intervention of a set of expert cognitive agents (such as story telling agents, assessment agents, stimulation agents or help agents). This InCA architecture has been applied for the design of K"InCA, an e-learning system aimed at helping people to learn and adopt knowledge-sharing management practices

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Guleva, Valentina, Egor Shikov, Klavdiya Bochenina, Sergey Kovalchuk, Alexander Alodjants, and Alexander Boukhanovsky. "Emerging Complexity in Distributed Intelligent Systems." Entropy 22, no. 12 (2020): 1437. http://dx.doi.org/10.3390/e22121437.

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Distributed intelligent systems (DIS) appear where natural intelligence agents (humans) and artificial intelligence agents (algorithms) interact, exchanging data and decisions and learning how to evolve toward a better quality of solutions. The networked dynamics of distributed natural and artificial intelligence agents leads to emerging complexity different from the ones observed before. In this study, we review and systematize different approaches in the distributed intelligence field, including the quantum domain. A definition and mathematical model of DIS (as a new class of systems) and it

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Lamia, Mahnane, and Hafidi Mohamed. "A Problem Solving Using Intelligent Social Network." International Journal of Web-Based Learning and Teaching Technologies 14, no. 3 (2019): 28–38. http://dx.doi.org/10.4018/ijwltt.2019070103.

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Nowadays, students are becoming familiar with the computer technology at a very early age. Moreover, the wide availability of the internet gives a new perspective to distance education making e-learning environments crucial to the future of education. Intelligent tutoring systems (ITSs) provide sophisticated tutoring systems using artificial intelligence techniques in computer programs to facilitate instruction. ITSs support problem solving by providing adaptive scaffolding in terms of feedback, guidance, problem selection and other types of help. Little attention has been devoted thus far to

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Rodríguez-Gracia, Diego, José A. Piedra-Fernández, Luis Iribarne, et al. "Microservices and Machine Learning Algorithms for Adaptive Green Buildings." Sustainability 11, no. 16 (2019): 4320. http://dx.doi.org/10.3390/su11164320.

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In recent years, the use of services for Open Systems development has consolidated and strengthened. Advances in the Service Science and Engineering (SSE) community, promoted by the reinforcement of Web Services and Semantic Web technologies and the presence of new Cloud computing techniques, such as the proliferation of microservices solutions, have allowed software architects to experiment and develop new ways of building open and adaptable computer systems at runtime. Home automation, intelligent buildings, robotics, graphical user interfaces are some of the social atmosphere environments s

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Capuano, Nicola, and Santi Caballé. "Adaptive Learning Technologies." AI Magazine 41, no. 2 (2020): 96–98. http://dx.doi.org/10.1609/aimag.v41i2.5317.

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Adaptive learning refers to technologies that dynamically adjust to the level or type of course content based on an individual’s abilities or skill attainment, in ways that accelerate a learner’s performance with both automated and instructor interventions. This column explores adaptive learning, its close relationship to artificial intelligence, and points to several results from artificial intelligence that have been used to build effective adaptive learning systems. The pairing of massive open online courses and adaptive learning has revealed new technical and pedagogical challenges that ar

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Liu, Xuanzhe, Shangguang Wang, Yun Ma, et al. "Operating Systems for Resource-adaptive Intelligent Software: Challenges and Opportunities." ACM Transactions on Internet Technology 21, no. 2 (2021): 1–19. http://dx.doi.org/10.1145/3425866.

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The past decades witnessed the fast and wide deployment of Internet. The Internet has bred the ubiquitous computing environment that is spanning the cloud, edge, mobile devices, and IoT. Software running over such a ubiquitous computing environment environment is eating the world. A recently emerging trend of Internet-based software systems is “ resource adaptive ,” i.e., software systems should be robust and intelligent enough to the changes of heterogeneous resources, both physical and logical, provided by their running environment. To keep pace of such a trend, we argue that some considerat

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Mohamed, Hafidi, and Bensebaa Taher. "Combining Expert Systems and Multiple Intelligences in an Adaptive and Intelligent Tutoring System." International Journal of Information Technology and Web Engineering 8, no. 3 (2013): 22–33. http://dx.doi.org/10.4018/ijitwe.2013070102.

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This paper describes an adaptive and intelligent tutoring system (AITS) based on multiple intelligences and expert system. Most of adaptive and intelligent tutoring systems based their adaptation to user’s skill level. Other learner features taken into account are background, hyperspace experience, preferences and interests. However, less attention was paid to multiple intelligences and their effects on learning. Moreover, to design AITS which can manage both different disciplinary domains and a guide for the learner is difficult. The specialization of the analysis treatments is responsible fo

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Bruha, Ivan. "DEFINING ADAPTIVE AND LEARNING SYSTEMS." Cybernetics and Systems 20, no. 1 (1989): 77–88. http://dx.doi.org/10.1080/01969728908902194.

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Li, Dong-Juan, Li Tang, and Yan-Jun Liu. "Adaptive intelligence learning for nonlinear chaotic systems." Nonlinear Dynamics 73, no. 4 (2013): 2103–9. http://dx.doi.org/10.1007/s11071-013-0926-4.

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Upadhyay, Ashwani Kumar, and Komal Khandelwal. "Artificial intelligence-based training learning from application." Development and Learning in Organizations: An International Journal 33, no. 2 (2019): 20–23. http://dx.doi.org/10.1108/dlo-05-2018-0058.

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Purpose This paper aims to discuss the rationale, theoretical foundation, application, and future of artificial intelligence (AI)-based training. Design/methodology/approach A review of relevant research papers, articles and case studies is done to highlight developments in research and practice. Findings AI-based training systems are smart, intelligent and expert in handling queries. These systems can curate content, grade, evaluate, and provide feedback to trainee, thus making learning adaptive and contextual. Practical implications Application of AI is vital in the field of training, as it

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Liang, Thow Yick. "Intelligence strategy: the evolutionary and co-evolutionary dynamics of intelligent human organizations and their interacting agents." Human Systems Management 23, no. 2 (2004): 137–49. http://dx.doi.org/10.3233/hsm-2004-23208.

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In the knowledge economy, the human minds are the most vital center of analysis. They are the complex adaptive systems capable of processing information, establishing knowledge structure, conceptualizing idea, and making decision. The intrinsic intelligence of the individual minds, as well as the organizational/collective intelligence, drives the dynamic of all human systems. Primarily, the local self-enrichment processes of the interacting agents are autopoietic. In addition, global forces are also present in all human organizations. The global forces are constructive only if they support the

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Nakrani, Naitik, and Maulin M. Joshi. "An adaptive motion planning algorithm for obstacle avoidance in autonomous vehicle parking." IAES International Journal of Artificial Intelligence (IJ-AI) 10, no. 3 (2021): 687. http://dx.doi.org/10.11591/ijai.v10.i3.pp687-697.

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In the recent era, machine learning-based autonomous vehicle parking and obstacle avoidance navigation have drawn increased attention. An intelligent design is needed to solve the autonomous vehicles related problems. Presently, autonomous parking systems follow path planning techniques that generally do not possess a quality and a skill of natural adapting behavior of a human. Most of these designs are built on pre-defined and fixed criteria. It needs to be adaptive with respect to the vehicle dynamics. A novel adaptive motion planning algorithm is proposed in this paper that incorporates obs

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Mowla, Nishat I., Nguyen H. Tran, Inshil Doh, and Kijoon Chae. "AFRL: Adaptive federated reinforcement learning for intelligent jamming defense in FANET." Journal of Communications and Networks 22, no. 3 (2020): 244–58. http://dx.doi.org/10.1109/jcn.2020.000015.

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Magnisalis, Ioannis, Stavros Demetriadis, and Anastasios Karakostas. "Adaptive and Intelligent Systems for Collaborative Learning Support: A Review of the Field." IEEE Transactions on Learning Technologies 4, no. 1 (2011): 5–20. http://dx.doi.org/10.1109/tlt.2011.2.

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Chen, Liang, Jianyan Sun, and Chunxiang Xu. "Regularized extreme learning machine–based intelligent adaptive control for uncertain nonlinear systems in networked control systems." Personal and Ubiquitous Computing 23, no. 3-4 (2019): 617–25. http://dx.doi.org/10.1007/s00779-019-01259-4.

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Gorbunovs, Aleksandrs, Zanis Timsans, Bruno Zuga, and Viktors Zagorskis. "Conceptual design of the new generation adaptive learning management system." International Journal of Engineering & Technology 7, no. 2.28 (2018): 129. http://dx.doi.org/10.14419/ijet.v7i2.28.12894.

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Taking into account that each new day an amount of daily processed data grows exponentially, it is obvious that knowledge society needs flexible, effective and high performing tools to retrieve, learn and apply necessary information. Learning management systems become more and more intelligent and adaptive. Learning analytics instruments give course developers a possibility to assess and analyze learners’ activities and behavior patterns within e-learning environment, allowing to propose them personalized self-paced learning path and types of learning objects. This paper discusses challenges i

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Rudas, Imre J. "Intelligent Engineering Systems." Journal of Advanced Computational Intelligence and Intelligent Informatics 4, no. 4 (2000): 237–39. http://dx.doi.org/10.20965/jaciii.2000.p0237.

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The "information revolution" of our time affects our entire generation. While a vision of the "Information Society," with its financial, legal, business, privacy, and other aspects has emerged in the past few years, the "traditional scene" of information technology, that is, industrial automation, maintained its significance as a field of unceasing development. Since the old-fashioned concept of "Hard Automation" applicable only to industrial processes of fixed, repetitive nature and manufacturing large batches of the same product1)was thrust to the background by keen market competition, the k

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Zhang, Jun-chang. "Adaptive Learning Environment System Based on Multi-event Driven Technology." International Journal of Emerging Technologies in Learning (iJET) 11, no. 11 (2016): 37. http://dx.doi.org/10.3991/ijet.v11i11.6250.

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Intelligent tutoring systems （ITSs） offer considerable flexibility in presentation of material and a greater ability to respond to idiosyncratic student needs. A multi agent system for adaptive learning environment is proposed in this paper. The system is composed of Open Agent Architecture and the Plan model. Teacher and student interaction was measured with the application of the system. The results prove that the system is an effective scheme to resolve the problem between dynamic students’ needs of resources and static teaching resources.

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Lee, Ching-Hung, and Yu-Ching Lin. "Robust Adaptive Control for Nonlinear Uncertain Systems Using Type-2 Fuzzy Neural Network System." Mathematical Problems in Engineering 2011 (2011): 1–25. http://dx.doi.org/10.1155/2011/604391.

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This paper proposes a novel intelligent control scheme using type-2 fuzzy neural network (type-2 FNN) system. The control scheme is developed using a type-2 FNN controller and an adaptive compensator. The type-2 FNN combines the type-2 fuzzy logic system (FLS), neural network, and its learning algorithm using the optimal learning algorithm. The properties of type-1 FNN system parallel computation scheme and parameter convergence are easily extended to type-2 FNN systems. In addition, a robust adaptive control scheme which combines the adaptive type-2 FNN controller and compensated controller i

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Bessa, Wallace M., Gerrit Brinkmann, Daniel A. Duecker, Edwin Kreuzer, and Eugen Solowjow. "A Biologically Inspired Framework for the Intelligent Control of Mechatronic Systems and Its Application to a Micro Diving Agent." Mathematical Problems in Engineering 2018 (December 30, 2018): 1–16. http://dx.doi.org/10.1155/2018/9648126.

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Mechatronic systems are becoming an intrinsic part of our daily life, and the adopted control approach in turn plays an essential role in the emulation of the intelligent behavior. In this paper, a framework for the development of intelligent controllers is proposed. We highlight that robustness, prediction, adaptation, and learning, which may be considered the most fundamental traits of all intelligent biological systems, should be taken into account within the project of the control scheme. Hence, the proposed framework is based on the fusion of a nonlinear control scheme with computational

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Zhang, Jingting, Chengzhi Yuan, Cong Wang, Wei Zeng, and Shi-Lu Dai. "Intelligent adaptive learning and control for discrete-time nonlinear uncertain systems in multiple environments." Neurocomputing 462 (October 2021): 31–45. http://dx.doi.org/10.1016/j.neucom.2021.07.046.

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Kasabov, Nikola. "The ECOS Framework and the ECO Learning Method for Evolving Connectionist Systems." Journal of Advanced Computational Intelligence and Intelligent Informatics 2, no. 6 (1998): 195–202. http://dx.doi.org/10.20965/jaciii.1998.p0195.

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This paper introduces a paradigm of connectionist architectures and an approach to building on-line, adaptive intelligent systems. This approach is called evolving connectionist systems (ECOS). EGOS evolve through incremental, on-line learning, both supervised and unsupervised. They can accommodate new input data, including new features, new classes, etc. The ECOS framework is presented and illustrated on a particular type of evolving neural networks - evolving fuzzy neural networks. The task of voice recognition and person identification is used as a case study.

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Liang, T. Y. "Intelligence strategy: The integrated 3C-OK framework of intelligent human organizations." Human Systems Management 23, no. 4 (2004): 203–11. http://dx.doi.org/10.3233/hsm-2004-23402.

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As humanity immerses deeper into the knowledge-intensive era, the mindset for leading, managing and structuring human organizations has to be transformed. Attention has been shifting from tangible to intangible assets. Human thinking systems, the sources where the world's most intense intrinsic intelligence originates become the key focal center. Intelligence and its dynamic are nonlinear. Arising from human consciousness are the two vital mental functions of awareness and mindfulness. These functions determine the quality of the mental state of the interacting agents. In addition, a high leve

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Mohammed, Mazin Abed, Dheyaa Ahmed Ibrahim, and Akbal Omran Salman. "Adaptive intelligent learning approach based on visual anti-spam email model for multi-natural language." Journal of Intelligent Systems 30, no. 1 (2021): 774–92. http://dx.doi.org/10.1515/jisys-2021-0045.

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Abstract Spam electronic mails (emails) refer to harmful and unwanted commercial emails sent to corporate bodies or individuals to cause harm. Even though such mails are often used for advertising services and products, they sometimes contain links to malware or phishing hosting websites through which private information can be stolen. This study shows how the adaptive intelligent learning approach, based on the visual anti-spam model for multi-natural language, can be used to detect abnormal situations effectively. The application of this approach is for spam filtering. With adaptive intellig

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Dounis. "Special Issue “Intelligent Control in Energy Systems”." Energies 12, no. 15 (2019): 3017. http://dx.doi.org/10.3390/en12153017.

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The editor of this special issue on “Intelligent Control in Energy Systems” have made an attempt to publish a book containing original technical articles addressing various elements of intelligent control in energy systems. The response to our call had 60 submissions, of which 27 were published submissions and 33 were rejections. This book contains 27 technical articles and one editorial. All have been written by authors from 15 countries (China, Netherlands, Spain, Tunisia, United States of America, Korea, Brazil, Egypt, Denmark, Indonesia, Oman, Canada, Algeria, Mexico, and Czech Republic),

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Hoang, Cong, Elena Avksentieva, and Yuriy Fedosov. "Forming an individual trajectory of teaching computer-aided design by means of an intelligent adaptive system." Ergodesign 2021, no. 1 (2021): 41–48. http://dx.doi.org/10.30987/2658-4026-2021-1-41-48.

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The aim of the work is to increase the efficiency of teaching computer-aided design of printed circuit boards of ship integrated control systems (CAD PCB SICS) with forming an individual learning path, in which there is a need to move from traditional teaching to intelligent adaptive training. The research method is to analyze the peculiarities of forming an individual trajectory of teaching CAD PCB. Research results and novelty:  an algorithm for implementing the training course at intelligent adaptive teaching CAD PCB SICS is developed; an algorithm for determining the comp

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Renn, Brenna N., Patricia A. Areán, Patrick J. Raue, Eugene Aisenberg, Emily C. Friedman, and Zoran Popović. "Modernizing Training in Psychotherapy Competencies With Adaptive Learning Systems: Proof of Concept." Research on Social Work Practice 31, no. 1 (2020): 90–100. http://dx.doi.org/10.1177/1049731520964854.

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Purpose: This proof-of-concept study assessed the feasibility, acceptability, and effectiveness of an intelligent tutoring system (ITS) as a classroom adjunct to improve training bachelor of social work (BSW) students in client engagement strategies. Methods: We codeveloped the ITS with 11 undergraduate students and pilot tested it with six BSW students enrolled in a class on telephone-based cognitive behavioral therapy (tCBT). Student competencies in tCBT were assessed by expert review of role-plays. We also examined time spent using ITS and relation with competency. Results: The majority of

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Darbari, Manuj, and Priya Sahai. "Adaptive e-Learning Multi-Agent Systems with Swarm Intelligence." International Journal of Applied Information Systems 7, no. 3 (2014): 16–20. http://dx.doi.org/10.5120/ijais14-451164.

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Dubey, Rahul, S. R. Samantaray, B. K. Panigrahi, and G. V. Venkoparao. "On-line Adaptive and Intelligent Distance Relaying Scheme for Power Network." International Journal of Emerging Electric Power Systems 16, no. 5 (2015): 473–89. http://dx.doi.org/10.1515/ijeeps-2015-0036.

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Abstract The paper presents an on-line sequential extreme learning machine (OS-ELM) based fast and accurate adaptive distance relaying scheme (ADRS) for transmission line protection. The proposed method develops an adaptive relay characteristics suitable to the changes in the physical conditions of the power systems. This can efficiently update the trained model on-line by partial training on the new data to reduce the model updating time whenever a new special case occurs. The effectiveness of the proposed method is validated on simulation platform for test system with two terminal parallel t

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Jafari, Mohammad, and Hao Xu. "Intelligent Control for Unmanned Aerial Systems with System Uncertainties and Disturbances Using Artificial Neural Network." Drones 2, no. 3 (2018): 30. http://dx.doi.org/10.3390/drones2030030.

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Stabilizing the Unmanned Aircraft Systems (UAS) under complex environment including system uncertainties, unknown noise and/or disturbance is so challenging. Therefore, this paper proposes an adaptive neural network based intelligent control method to overcome these challenges. Based on a class of artificial neural network, named Radial Basis Function (RBF) networks an adaptive neural network controller is designed. To handle the unknown dynamics and uncertainties in the system, firstly, we develop a neural network based identifier. Then, a neural network based controller is generated based on

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