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Relevant bibliographies by topics / Artificial intelligent algorithms

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Academic literature on the topic 'Artificial intelligent algorithms'

Author: Grafiati

Published: 28 May 2022

Last updated: 31 July 2025

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Journal articles on the topic "Artificial intelligent algorithms"

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BUITEN, Miriam C. "Towards Intelligent Regulation of Artificial Intelligence." European Journal of Risk Regulation 10, no. 1 (2019): 41–59. http://dx.doi.org/10.1017/err.2019.8.

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Artificial intelligence (AI) is becoming a part of our daily lives at a fast pace, offering myriad benefits for society. At the same time, there is concern about the unpredictability and uncontrollability of AI. In response, legislators and scholars call for more transparency and explainability of AI. This article considers what it would mean to require transparency of AI. It advocates looking beyond the opaque concept of AI, focusing on the concrete risks and biases of its underlying technology: machine-learning algorithms. The article discusses the biases that algorithms may produce through

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Guo, Aipeng, and Chunhui Yuan. "Network Intelligent Control and Traffic Optimization Based on SDN and Artificial Intelligence." Electronics 10, no. 6 (2021): 700. http://dx.doi.org/10.3390/electronics10060700.

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For telecom operators, it is of great significance to employ artificial intelligence (AI) and big data technology in a software-defined network (SDN) in order to achieve intelligent network control, traffic management and optimization. This paper proposes a solution for intelligent work control and traffic optimization. This paper is mainly focused on SDN-based network traffic algorithm optimization and experimental verification. In this paper, we design a network control mechanism for network intelligent control as well as solutions for traffic optimization based on SDN and artificial intelli

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Ke, Yihan. "Comparative Analysis of Path Planning Algorithms and Prospects for Practical Application." Highlights in Science, Engineering and Technology 52 (July 4, 2023): 202–7. http://dx.doi.org/10.54097/hset.v52i.8889.

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Path planning, as an important applications of artificial intelligence technology in the field of intelligent transportation, has a wide range of application prospects in achieving efficient, intelligent, and safe travel. This paper first introduces the importance of path planning technology in the field of transportation, and then discusses the development of path planning from two aspects: traditional methods and new methods based on artificial intelligence. In terms of traditional methods, the principles and advantages and disadvantages of methods such as Dijkstra's algorithm, A* algorithm,

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Zhao, Ziming, and Jinyu Chen. "Application of artificial intelligence technology in the economic development of urban intelligent transportation system." PeerJ Computer Science 11 (March 20, 2025): e2728. https://doi.org/10.7717/peerj-cs.2728.

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With the rapid development of the social economy and the gradual improvement of residents’ living standards, the increasing number of urban cars has exacerbated urban traffic congestion. This article analyzed the application of artificial intelligence (AI) technology in five aspects of urban intelligent transportation systems. Artificial intelligence technology was used in traffic data collection and processing to provide accurate data support for traffic decision-making. A traffic flow prediction model was established for traffic flow prediction and optimized scheduling algorithms were used t

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Lie, Luo. "Heuristic Artificial Intelligent Algorithm for Genetic Algorithm." Key Engineering Materials 439-440 (June 2010): 516–21. http://dx.doi.org/10.4028/www.scientific.net/kem.439-440.516.

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A genetic algorithm is a search technique used in computing to find exact or approximate solutions to optimization and search problems. Genetic algorithms are categorized as global search heuristics. Genetic algorithms are a particular class of evolutionary algorithms that use techniques inspired by evolutionary biology such as inheritance, mutation, selection, and crossover.

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Lin, Yangqi, Qian Luo, and Yuzhao Qian. "Investigation of Artificial Intelligence algorithms in education." Applied and Computational Engineering 16, no. 1 (2023): 180–84. http://dx.doi.org/10.54254/2755-2721/16/20230886.

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The application of Artificial Intelligence (AI) in education has garnered increasing attention in recent years. This study investigates the primary methods of AI in education, including The Teaching Machine System, Intelligent Tutoring Systems, Intelligent Educational Systems, and the Intelligent College Student Comprehensive Quality Evaluation Model. The Teaching Machine System employs pre-defined rules and algorithms to deliver personalized instruction to students. Intelligent Tutoring Systems use AI algorithms to provide real-time feedback and guidance to students, tailoring the learning ex

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Gong, Fanghai. "Application of Artificial Intelligence Computer Intelligent Heuristic Search Algorithm." Advances in Multimedia 2022 (September 24, 2022): 1–12. http://dx.doi.org/10.1155/2022/5178515.

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In order to transform three-dimensional space path planning into two-dimensional plane path planning problem and greatly reduce the search time, an intelligent heuristic search algorithm based on artificial intelligence is proposed. The heuristic search algorithm is analyzed and introduced, and A is chosen. A two-dimensional spatial environment model of picking robot path planning is investigated, and a spatial model of picking robot path planning is established by raster method. Then, considering the whole day operation time, the whole day operation time is divided into several periods. With

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Peng, Qiang, Renjun Zhan, Husheng Wu, and Meimei Shi. "Comparative Study of Wolf Pack Algorithm and Artificial Bee Colony Algorithm." International Journal of Swarm Intelligence Research 15, no. 1 (2024): 1–24. http://dx.doi.org/10.4018/ijsir.352061.

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Swarm intelligence optimization algorithms have been widely used in the fields of machine learning, process control and engineering prediction, among which common algorithms include ant colony algorithm (ACO), artificial bee colony algorithm (ABC) and particle swarm optimization (PSO). Wolf pack algorithm (WPA) as a newer swarm intelligence optimization algorithm has many similarities with ABC. In this paper, the basic principles, algorithm implementation processes, and related improvement strategies of these two algorithms were described in detail; A comparative analysis of their performance

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Wu, Suzhen. "Design of Intelligent Nursing System Based on Artificial Intelligence." Journal of Sensors 2022 (August 21, 2022): 1–5. http://dx.doi.org/10.1155/2022/7427968.

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As the number of the elderly population and the population dependency ratio increase year by year, the issue of old-age care has become the focus. However, due to the shortage of carers and the large-scale and expensive auxiliary equipment for the elderly, it is difficult to give thoughtful care to all the elderly. In view of the above background, this paper designs a set of intelligent nursing system for the elderly based on artificial intelligence (AI) algorithms, which mainly includes sensor terminals and AI processing algorithms. Among them, the sensor terminal mainly includes two parts: v

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Sun, Jingran, Yuyin Zhang, Fangjia Fu, Liyan Kang, and Junxu Ma. "Research and Prospect of Intelligent Workshop AGV Path Planning Algorithm." Journal of Engineering Research and Reports 26, no. 7 (2024): 71–80. http://dx.doi.org/10.9734/jerr/2024/v26i71195.

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Path planning algorithm is one of the core algorithms for automatic guided vehicle（AGV）to complete the autonomous task of intelligent workshop. The research status of grid method and Viewable method in environment modeling at home and abroad is described. The research results of traditional path search algorithms such as artificial potential field method, Dijstra algorithm and A* algorithm are analyzed and compared with intelligent algorithms such as particle swarm optimization algorithm, ant colony algorithm and genetic algorithm. The analysis finds that in the face of complex workshop enviro

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Dissertations / Theses on the topic "Artificial intelligent algorithms"

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Wakelam, Mark. "Intelligent hybrid approach for integrated design." Thesis, University of Nottingham, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.263942.

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Qi, Dehu. "Multi-agent systems : integrating reinforcement learning, bidding and genetic algorithms /." free to MU campus, to others for purchase, 2002. http://wwwlib.umi.com/cr/mo/fullcit?p3060133.

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Yang, Jianhua. "Intelligent data mining using artificial neural networks and genetic algorithms : techniques and applications." Thesis, University of Warwick, 2010. http://wrap.warwick.ac.uk/3831/.

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Data Mining (DM) refers to the analysis of observational datasets to find relationships and to summarize the data in ways that are both understandable and useful. Many DM techniques exist. Compared with other DM techniques, Intelligent Systems (ISs) based approaches, which include Artificial Neural Networks (ANNs), fuzzy set theory, approximate reasoning, and derivative-free optimization methods such as Genetic Algorithms (GAs), are tolerant of imprecision, uncertainty, partial truth, and approximation. They provide flexible information processing capability for handling real-life situations.

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Mailah, Musa. "Intelligent active force control of a rigid robot arm using neural network and iterative learning algorithms." Thesis, University of Dundee, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.269529.

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Wong, Wing-ki Vicky. "An immunity-based distributed multiagent control framework." Click to view the E-thesis via HKUTO, 2006. http://sunzi.lib.hku.hk/hkuto/record/B37314348.

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Nikolaiev, Y., Інна Олексіївна Зайцева, Инна Алексеевна Зайцева, and Inna Oleksiivna Zaitseva. "Künstliche intelligenz." Thesis, Sumy State University, 2020. https://essuir.sumdu.edu.ua/handle/123456789/77844.

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Künstliche Intelligenz hat sich im letzten Jahrzehnt von einem Science-Fiction-Traum zu einem kritischen Teil unseres Alltags entwickelt. Wir verwenden Künstliche-Intelligenz -Systeme, um mit unseren Handys über Siri zu interagieren, Autos wie Teslas zu interpretieren. Künstlich intelligente Algorithmen sind hier, sie haben unser Leben bereits zum Besseren oder Schlechteren verändert. Aber das ist nur der Anfang, und eines Tages werden wir 2019 auf Künstliche Intelligenz zurückblicken und darüber lachen, wie primitiv es war. In erster Linie sind KI-Systeme bereits darauf vorbereitet, Millione

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Wong, Wing-ki Vicky, and 黃穎琪. "An immunity-based distributed multiagent control framework." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2006. http://hub.hku.hk/bib/B37314348.

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Yu, Chen-Ping. "Computational model of MST neuron receptive field and interaction effect for the perception of self-motion /." Online version of thesis, 2008. http://hdl.handle.net/1850/9588.

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MAZZIA, VITTORIO. "Machine Learning Algorithms and their Embedded Implementation for Service Robotics Applications." Doctoral thesis, Politecnico di Torino, 2022. http://hdl.handle.net/11583/2968456.

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Burdelis, Mauricio Alexandre Parente. "Ajuste de taxas de mutação e de cruzamento de algoritmos genéticos utilizando-se inferências nebulosas." Universidade de São Paulo, 2009. http://www.teses.usp.br/teses/disponiveis/3/3141/tde-14082009-180444/.

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Neste trabalho foi realizada uma proposta de utilização de Sistemas de Inferência Nebulosos para controlar, em tempo de execução, parâmetros de Algoritmos Genéticos. Esta utilização busca melhorar o desempenho de Algoritmos Genéticos diminuindo, ao mesmo tempo: a média de iterações necessárias para que um Algoritmo Genético encontre o valor ótimo global procurado; bem como diminuindo o número de execuções do mesmo que não são capazes de encontrar o valor ótimo global procurado, nem mesmo para quantidades elevadas de iterações. Para isso, foram analisados os resultados de diversos experimentos

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Books on the topic "Artificial intelligent algorithms"

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Silhavy, Radek, ed. Artificial Intelligence Methods in Intelligent Algorithms. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-19810-7.

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Silhavy, Radek, ed. Artificial Intelligence and Algorithms in Intelligent Systems. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-91189-2.

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B, Verbruggen H., Babuška Robert, and Zimmermann H. J. 1934-, eds. Fuzzy algorithms for control. Kluwer Academic Publishers, 1999.

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Różewski, Przemysław. Intelligent Open Learning Systems: Concepts, Models and Algorithms. Springer-Verlag GmbH Berlin Heidelberg, 2011.

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Sharma, Teena, and Nishchal K. Verma. Artificial Intelligent Algorithms for Image Dehazing and Non-Uniform Illumination Enhancement. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-2011-8.

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Tian, Jing, and Li Chen. Intelligent image and video interpretation: Algorithms and applications. Information Science Reference, 2013.

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Paul, Casasent David, and Society of Photo-optical Instrumentation Engineers., eds. Intelligent robots and computer vision XIII: Algorithms and computer vision : 31 October-2 November 1994. SPIE, 1994.

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Ruan, Da. Intelligent Hybrid Systems: Fuzzy Logic, Neural Networks, and Genetic Algorithms. Springer US, 1997.

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Paul, Casasent David, and Society of Photo-optical Instrumentation Engineers., eds. Intelligent robots and computer vision XIII: Algorithms and computer vision : 31 October-2 November 1994, Boston, Massachusetts. SPIE, 1994.

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Paul, Casasent David, Society of Photo-optical Instrumentation Engineers., and Automated Imaging Association, eds. Intelligent robots and computer vision XII: Algorithms and techniques : 7-9 September 1993, Boston, Massachusetts. SPIE, 1993.

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Book chapters on the topic "Artificial intelligent algorithms"

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Silva, Carla Sofia R., and Jose Manuel Fonseca. "Artificial Intelligence and Algorithms in Intelligent Systems." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-91189-2_30.

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Zhang, Yuhong, and Umer Nauman. "Artificial Unintelligence: Anti-intelligence of Intelligent Algorithms." In Intelligence Science II. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-01313-4_35.

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Gupta, Rakshit, Yogesh Mahajan, Punit Mukesh Ahuja, and Jyoti Ramteke. "Portfolio Management Using Artificial Intelligence." In Algorithms for Intelligent Systems. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-1059-5_24.

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Kaur, Prabhjot, and Praveen Kumar Khosla. "Artificial Intelligence Based Glaucoma Detection." In Algorithms for Intelligent Systems. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-15-1100-4_14.

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Bahekar, Kirti Bala. "Comprehensive Analysis of Classification Techniques Based on Artificial Immune System and Artificial Neural Network Algorithms." In Algorithms for Intelligent Systems. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-4604-8_68.

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Habib, Fakih Awab, Ghare Shifa Shakil, Shaikh Sabreen Mohd Iqbal, and Shaikh Tasmia Abdul Sajid. "Self-Diagnosis Medical Chatbot Using Artificial Intelligence." In Algorithms for Intelligent Systems. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-6707-0_57.

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Barkavi, R., G. Yamuna, and C. Jayaram. "Artificial Intelligence: Revolution in Assisted Reproductive Technology." In Algorithms for Intelligent Systems. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-3485-0_76.

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Oumaima, Derouech, Lachgar Mohamed, Hrimech Hamid, and Hanine Mohamed. "Application of Artificial Intelligence in Virtual Reality." In Algorithms for Intelligent Systems. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-99-9436-6_6.

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Fountis, Anastasios, and Christos Lemonakis. "Artificial Intelligence (ΑΙ) in Education—Current Trends." In Algorithms for Intelligent Systems. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-99-8976-8_18.

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Goswami, Ramesh Chandra, Hiren Joshi, and Sunil Gautam. "Artificial Intelligence-Based Internet of Things Security." In Algorithms for Intelligent Systems. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-6645-5_9.

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Conference papers on the topic "Artificial intelligent algorithms"

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Tian, Liang. "Artificial Neural Network Based Improved Pelican Optimization Algorithm for 3D Printed Footwear Products Design in Artificial Intelligence." In 2024 International Conference on Intelligent Algorithms for Computational Intelligence Systems (IACIS). IEEE, 2024. http://dx.doi.org/10.1109/iacis61494.2024.10721927.

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Shanthi, K., and S. Manimekalai. "Classification of Cervical Cancer using Artificial Neural Network." In 2024 International Conference on Intelligent Algorithms for Computational Intelligence Systems (IACIS). IEEE, 2024. http://dx.doi.org/10.1109/iacis61494.2024.10721706.

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Tang, Haotian. "Intelligent Vision Testing Technology for Gesture Recognition Based on Artificial Intelligence Algorithms." In 2024 International Conference on Data Science and Network Security (ICDSNS). IEEE, 2024. http://dx.doi.org/10.1109/icdsns62112.2024.10691206.

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Qin, Wenxin. "Construction of Computer Network Management System based on NETCONF and Artificial Intelligence." In 2024 International Conference on Intelligent Algorithms for Computational Intelligence Systems (IACIS). IEEE, 2024. http://dx.doi.org/10.1109/iacis61494.2024.10721622.

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Zhang, Xuxia, Yang Ding, Tongjun Jiang, Weijie Chen, and Jian Wang. "Information Network Security Situation Awareness Based on Artificial Intelligence and Machine Learning Algorithms." In 2024 International Conference on Intelligent Algorithms for Computational Intelligence Systems (IACIS). IEEE, 2024. http://dx.doi.org/10.1109/iacis61494.2024.10721626.

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Liu, Yang. "Intelligent Building Optimization Design Based on Artificial Neural Network with Tasmanian Devil Optimization." In 2024 International Conference on Intelligent Algorithms for Computational Intelligence Systems (IACIS). IEEE, 2024. http://dx.doi.org/10.1109/iacis61494.2024.10721806.

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Liu, Tao, and Bohan Zhang. "A UAV-Based Remote Sensing Image Automatic Monitoring System Empowered by Artificial Intelligence." In 2024 International Conference on Intelligent Algorithms for Computational Intelligence Systems (IACIS). IEEE, 2024. http://dx.doi.org/10.1109/iacis61494.2024.10721807.

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Bhajantri, Lokesh B., Mohammed Rehan, and Bandenawaz F. B. "Artificial Intelligence and Machine Learning Approach Recommendation System in Internet of Medical Things." In 2024 International Conference on Intelligent Algorithms for Computational Intelligence Systems (IACIS). IEEE, 2024. http://dx.doi.org/10.1109/iacis61494.2024.10722011.

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Xu, Xingque, and Jiawei Wei. "Artificial Intelligence and Automated Operation and Maintenance Technology in Wireless Network Power Systems." In 2024 International Conference on Intelligent Algorithms for Computational Intelligence Systems (IACIS). IEEE, 2024. http://dx.doi.org/10.1109/iacis61494.2024.10721787.

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Wang, Hua. "Intelligent Prediction and Training Optimization of Sports using Enhanced Whale Optimized Artificial Neural Network." In 2024 International Conference on Intelligent Algorithms for Computational Intelligence Systems (IACIS). IEEE, 2024. http://dx.doi.org/10.1109/iacis61494.2024.10721754.

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Reports on the topic "Artificial intelligent algorithms"

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Rinuado, Christina, William Leonard, Christopher Morey, Theresa Coumbe, Jaylen Hopson, and Robert Hilborn. Artificial intelligence (AI)–enabled wargaming agent training. Engineer Research and Development Center (U.S.), 2024. http://dx.doi.org/10.21079/11681/48419.

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Fiscal Year 2021 (FY21) work from the Engineer Research and Development Center Institute for Systems Engineering Research lever-aged deep reinforcement learning to develop intelligent systems (red team agents) capable of exhibiting credible behavior within a military course of action wargaming maritime framework infrastructure. Building from the FY21 research, this research effort sought to explore options to improve upon the wargaming framework infrastructure and to investigate opportunities to improve artificial intelligence (AI) agent behavior. Wargaming framework infrastructure enhancement

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Willson. L51756 State of the Art Intelligent Control for Large Engines. Pipeline Research Council International, Inc. (PRCI), 1996. http://dx.doi.org/10.55274/r0010423.

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Computers have become a vital part of the control of pipeline compressors and compressor stations. For many tasks, computers have helped to improve accuracy, reliability, and safety, and have reduced operating costs. Computers excel at repetitive, precise tasks that humans perform poorly - calculation, measurement, statistical analysis, control, etc. Computers are used to perform these type of precise tasks at compressor stations: engine / turbine speed control, ignition control, horsepower estimation, or control of complicated sequences of events during startup and/or shutdown. For other task

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Pasupuleti, Murali Krishna. AI-Driven Automation: Transforming Industry 5.0 withMachine Learning and Advanced Technologies. National Education Services, 2025. https://doi.org/10.62311/nesx/rr225.

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Abstract: This article delves into the transformative role of artificial intelligence (AI) and machine learning (ML) in shaping Industry 5.0, a paradigm centered on human- machine collaboration, sustainability, and resilient industrial ecosystems. Beginning with the evolution from Industry 4.0 to Industry 5.0, it examines core AI technologies, including predictive analytics, natural language processing, and computer vision, which drive advancements in manufacturing, quality control, and adaptive logistics. Key discussions include the integration of collaborative robots (cobots) that enhance hu

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Blanchard, Alexander, and Laura Bruun. Bias in Military Artificial Intelligence. Stockholm International Peace Research Institute, 2024. https://doi.org/10.55163/cjft9557.

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To support states involved in the policy debate on military artificial intelligence (AI), this background paper provides a deeper examination of the issue of bias in military AI. Three insights arise. First, policymakers could usefully develop an account of bias in military AI that captures shared concern around unfairness. If so, ‘bias in military AI’ might be taken to refer to the systemically skewed performance of a military AI system that leads to unjustifiably different behaviours—which may perpetuate or exacerbate harmful or discriminatory outcomes—depending on such social characteristic

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Lewis, Dustin, ed. A Compilation of Materials Apparently Reflective of States’ Views on International Legal Issues pertaining to the Use of Algorithmic and Data-reliant Socio-technical Systems in Armed Conflict. Harvard Law School Program on International Law and Armed Conflict, 2020. http://dx.doi.org/10.54813/cawz3627.

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This document is a compilation of materials that at least appear to be reflective of one or more states’ views on international legal issues pertaining to the actual or possible use of algorithmic and data-reliant socio-technical systems in armed conflict. In September of 2018, the Harvard Law School Program on International Law and Armed Conflict (HLS PILAC) commenced a project titled “International Legal and Policy Dimensions of War Algorithms: Enduring and Emerging Concerns.”[1] The project builds on the program’s earlier research and policy initiative on war-algorithm accountability. A goa

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Asker, John, Chaim Fershtman, and Ariel Pakes. Artificial Intelligence and Pricing: The Impact of Algorithm Design. National Bureau of Economic Research, 2021. http://dx.doi.org/10.3386/w28535.

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Mazari, Mehran, Yahaira Nava-Gonzalez, Ly Jacky Nhiayi, and Mohamad Saleh. Smart Highway Construction Site Monitoring Using Artificial Intelligence. Mineta Transportation Institute, 2025. https://doi.org/10.31979/mti.2025.2336.

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Construction is a large sector of the economy and plays a significant role in creating economic growth and national development,and construction of transportation infrastructure is critical. This project developed a method to detect, classify, monitor, and track objects during the construction, maintenance, and rehabilitation of transportation infrastructure by using artificial intelligence and a deep learning approach. This study evaluated the performance of AI and deep learning algorithms to compare their performance in detecting and classifying the equipment in various construction scenes.

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Buchanan, Ben. The AI Triad and What It Means for National Security Strategy. Center for Security and Emerging Technology, 2020. http://dx.doi.org/10.51593/20200021.

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One sentence summarizes the complexities of modern artificial intelligence: Machine learning systems use computing power to execute algorithms that learn from data. This AI triad of computing power, algorithms, and data offers a framework for decision-making in national security policy.

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Hashemi, Sara, Hengameh Ferdosian, and Hadi Zamanian. Accuracy of artificial intelligence in CT interpretation in covid-19: a systematic review protocol for systematic review and meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2021. http://dx.doi.org/10.37766/inplasy2021.10.0048.

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Review question / Objective: The aim of this systematic review is to compare the accuracy of artificial intelligence algorithms with radiologist panels in CT interpretation in covid-19. Condition being studied: COVID-19 disease was reported as the cause of the outbreak of pneumonia at the end of 2019. One of the main complications of COVID-19 is pulmonary involvement which could be diagnosed by CT-scan dominantly. Because of the increasing rate of these patients along with considering patients in remote areas, CT interpretations are a heavy burden on radiologists. Therefore artificial intellig

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Liao, Han. New heuristic algorithm to improve the Minimax for Gomoku artificial intelligence. Iowa State University, 2019. http://dx.doi.org/10.31274/cc-20240624-1052.

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