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Littérature scientifique sur le sujet « Hybrid Analytical Intelligence »

Auteur : Grafiati

Publié le 2 juin 2025

Mis à jour le 31 juillet 2025

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Articles de revues sur le sujet "Hybrid Analytical Intelligence"

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Shiriaev, Е. М., А. S. Nazarov, N. N. Kucherov, and М. G. Babenko. "Analytical review of confidential artificial intelligence: methods and algorithms for deployment in cloud computing." Programmirovanie, no. 4 (December 2, 2024): 27–40. https://doi.org/10.31857/s0132347424040036.

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The technologies of artificial intelligence and cloud systems have recently been actively developed and implemented. In this regard, the issue of their joint use, which has been topical for several years, has become more acute. The problem of data privacy preservation in cloud computing acquired the status of critical long before the necessity of their joint use with artificial intelligence, which made it even more complicated. This paper presents an overview of both the artificial intelligence and cloud computing techniques themselves, as well as methods to ensure data privacy. The review con

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Manoilo, A. V. ""Hybrid diplomacy": on the production of personnel in the field of countering foreign information and hybrid wars." Diplomaticheskaja sluzhba (Diplomatic Service), no. 2 (March 31, 2023): 130–39. http://dx.doi.org/10.33920/vne-01-2302-05.

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This article is devoted to the issues of personnel training to counter the infected and hybrid free war against the Russian Federation in connection with the start of the Special Military Operation in Ukraine. It is noted that programs such as "Information and hybrid wars" are a structure for the formation in the Russian Federation of a nationwide system to counter information and hybrid war. In modern programs for training specialists in countering information and hybrid wars of great importance for international and analytical work, the main justifications and methods are disclosed in the co

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Yu, Ming, Haotian Lu, Hai Wang, Chenyu Xiao, Dun Lan, and Junjie Chen. "Computational Intelligence-Based Prognosis for Hybrid Mechatronic System Using Improved Wiener Process." Actuators 10, no. 9 (2021): 213. http://dx.doi.org/10.3390/act10090213.

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In this article, a fast krill herd algorithm is developed for prognosis of hybrid mechatronic system using the improved Wiener degradation process. First, the diagnostic hybrid bond graph is used to model the hybrid mechatronic system and derive global analytical redundancy relations. Based on the global analytical redundancy relations, the fault signature matrix and mode change signature matrix for fault and mode change isolation can be obtained. Second, in order to determine the true faults from the suspected fault candidates after fault isolation, a fault estimation method based on adaptive

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Elling, John W., Sharbari Lahiri, Jason P. Luck, et al. "Peer Reviewed: Hybrid Artificial Intelligence Tools for Assessing GC Data." Analytical Chemistry 69, no. 13 (1997): 409A—415A. http://dx.doi.org/10.1021/ac971691t.

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Banerjee, Debalina, Jagadeesh Putta, and Rama Mohan Rao P. "Heuristic Driven Hybrid Analytical-Artificial Intelligence Concept for Risk Prediction in Construction Megaprojects." International Review of Civil Engineering (IRECE) 12, no. 6 (2021): 398. http://dx.doi.org/10.15866/irece.v12i6.20864.

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Hingant, Javier, Marcelo Zambrano, Francisco J. Pérez, Israel Pérez, and Manuel Esteve. "HYBINT: A Hybrid Intelligence System for Critical Infrastructures Protection." Security and Communication Networks 2018 (August 27, 2018): 1–13. http://dx.doi.org/10.1155/2018/5625860.

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Cyberattacks, which consist of exploiting security vulnerabilities of computer networks and systems for any kind of malicious purpose (e.g., extortion, data steal, assets hijacking), have been continuously increasing worldwide in recent years. Cyberspace appears today as a new battlefield, along with physical world scenarios (land, sea, air, and space), for the organizations defence and security. Besides, by the fact that attacks from the physical world may have significant implications in the cyber world and vice versa, these dimensions cannot be understood independently. However, the most co

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ZHANG, Y. Y., and P. S. P. WANG. "ANALYTICAL COMPARISON OF THINNING ALGORITHMS." International Journal of Pattern Recognition and Artificial Intelligence 07, no. 05 (1993): 1227–46. http://dx.doi.org/10.1142/s0218001493000601.

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This paper deals with analyzing and comparing several key thinning algorithms in terms of various different methodologies. From these analyses and comparisons, a new sequential model thinning algorithm using heuristic, hybrid methods is presented. It intends to produce, based on past experience, thinned skeletons of thickness one from input patterns, keep connectivity, and eliminate unnecessary pixels. Several illustrative examples on various patterns were tested and the results compared. The parallel model thinning algorithm is still open.

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Moser, Benjamin L., Joshua A. Gordon, and Andrew J. Petruska. "Unified Parameterization and Calibration of Serial, Parallel, and Hybrid Manipulators." Robotics 10, no. 4 (2021): 124. http://dx.doi.org/10.3390/robotics10040124.

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In this work, we present methods allowing parallel, hybrid, and serial manipulators to be analyzed, calibrated, and controlled with the same analytical tools. We introduce a general approach to describe any robotic manipulator using established serial-link representations. We use this framework to generate analytical kinematic and calibration Jacobians for general manipulator constructions using null space constraints and extend the methods to hybrid manipulator types with complex geometry. We leverage the analytical Jacobians to develop detailed expressions for post-calibration pose uncertain

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Bryndin, Evgeny. "Functional and Harmonious Selforganization of Large Intellectual Agent Ensembles with Smart Hybrid Competencies via Wireless and Mobile Networks." International Journal of Wireless & Mobile Networks 13, no. 05 (2021): 1–13. http://dx.doi.org/10.5121/ijwmn.2021.13501.

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Artificial intelligence of large ensembles of intelligent agents in terms of computing power surpasses human intelligence. He is capable of artificial thinking and understanding. Giant ensembles of intellectual agents with artificial consciousness and intelligence are able, for the results set by the person necessary for him, to find solutions for their obtaining on the basis of professional competence and experience accumulation. The professional competence of artificial intelligence is the ability to use technologies, including computer vision, natural language processing, speech recognition

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Akinyede, Akinyede, Josephine Adenike, Akinyede Akinyede, Temitope Temitope, Alake Alake, and Temitope John. "A Review of Analytical and Intelligent Methods for Optimal Distributed Generation Placement in Modern Distribution Networks: Techniques, Challenges, and Future Directions." International Journal of Advances in Engineering and Management 6, no. 11 (2024): 108–17. https://doi.org/10.35629/5252-0611108117.

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This comprehensive review examines the state-ofthe-art methodologies for optimal Distributed Generation (DG) placement in modern distribution networks, addressing the critical challenges of power quality enhancement and system reliability. The study systematically analyses various approaches including analytical methods, optimization techniques, artificial intelligence algorithms, graph theory applications, simulation-based methods, and hybrid solutions. Recent research indicates that optimized DG placement can achieve up to 60% reduction in system losses and 15% improvement in voltage profile

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Thèses sur le sujet "Hybrid Analytical Intelligence"

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Kim, Intaek. "A Hybrid analytical/intelligent methodology for sensor fusion." Diss., Georgia Institute of Technology, 1992. http://hdl.handle.net/1853/13743.

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Akinade, Olugbenga Olawale. "BIM-based software for construction waste analytics using artificial intelligence hybrid models." Thesis, University of the West of England, Bristol, 2017. http://eprints.uwe.ac.uk/31762/.

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The Construction industry generates about 30% of the total waste in the UK. Current high landfill cost and severe environmental impact of waste reveals the need to reduce waste generated from construction activities. Although literature reveals that the best approach to Construction Waste (CW) management is minimization at the design stage, current tools are not robust enough to support architects and design engineers. Review of extant literature reveals that the key limitations of existing CW management tools are that they are not integrated with the design process and that they lack Building

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Moscoso-Zea, Oswaldo. "A Hybrid Infrastructure of Enterprise Architecture and Business Intelligence & Analytics to Empower Knowledge Management in Education." Doctoral thesis, Universidad de Alicante, 2019. http://hdl.handle.net/10045/97408.

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The large volumes of data (Big Data) that are generated on a global scale and within organizations along with the knowledge that resides in people and in business processes makes organizational knowledge management (KM) very complex. A right KM can be a source of opportunities and competitive advantage for organizations that use their data intelligently and subsequently generate knowledge with them. Two of the fields that support KM and that have had accelerated growth in recent years are business intelligence (BI) and enterprise architecture (EA). On the one hand, BI allows taking advantage o

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Van, den Berg Matthias Adriaan. "The intelligence regime in South Africa (1994-2014) : an analytical perspective / Matthias Adriaan van den Berg." Thesis, 2014. http://hdl.handle.net/10394/13438.

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Intelligence, having espionage as its roots, is sometimes misunderstood due to its secret nature. It is due to this that intelligence as a vital component in a state, could be misused by the political regime through less democratic practices that infringe on human rights and the rule of law. The quest of this study (which is not classified, to make the research findings available to both practitioners and scholars of intelligence studies), is to attempt to contribute to the theory and understanding of intelligence studies as a sub-field within the political science in describing, explaining an

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Chapitres de livres sur le sujet "Hybrid Analytical Intelligence"

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Goud B, Srikanth, Ankit Kumar, Shyam Akashe, Seelam VSV Prabhu Deva Kumar, and Ch Rami Reddy. "Analytical Study of DC-to-DC Power Converter." In Hybrid Intelligence for Smart Grid Systems. CRC Press, 2021. http://dx.doi.org/10.1201/9781003143802-5.

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Chanda, Bidisha, Pradeep Kumar Mallick, and Gyoo-Soo Chae. "An Analytical Study of the Role of M-IoT in Healthcare Domain." In Hybrid Artificial Intelligence and IoT in Healthcare. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-2972-3_4.

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Kovalerchuk, Boris. "Enhancement of Cross Validation Using Hybrid Visual and Analytical Means with Shannon Function." In Studies in Computational Intelligence. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-31041-7_29.

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Panwar, Surya Nandan, Saliya Goyal, and Prafulla Bafna. "Analytical Study of Starbucks Using Clustering." In Hybrid Intelligent Systems. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-27409-1_93.

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Pawar, Samruddhi, Shubham Agarwal, and Prafulla Bafna. "Analytical Study of Effects on Business Sectors During Pandemic-Data Mining Approach." In Hybrid Intelligent Systems. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-27409-1_94.

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Heino, Timi, Sampsa Rauti, Robin Carlsson, and Ville Leppänen. "Study of Third-Party Analytics Services on University Websites." In Hybrid Intelligent Systems. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-27409-1_117.

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Chang, Wui-Lee, Sing-Ling Ong, and Jill Ling. "Incremental Cluster Interpretation with Fuzzy ART in Web Analytics." In Hybrid Intelligent Systems. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-27409-1_46.

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Schuchter, Florian, Katharina Bause, and Albert Albers. "Intelligent Data Analytics with Artificial Intelligence for Hybrid Engine Restart." In Proceedings. Springer Fachmedien Wiesbaden, 2022. http://dx.doi.org/10.1007/978-3-658-37011-4_6.

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WU, Siegfried Zhiqiang. "Matching Between New Generation AI Technologies and Urban Demands." In The Urban Book Series. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-2560-4_6.

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Abstract This chapter examines the alignment between next-generation AI (AI 2.0) technology and the requirements of urban environments, with a focus on the application of AI 2.0 across ten key urban functions: nature, governance, housing, mobility, commerce, healthcare, education, industry, infrastructure, and innovation. By developing a matrix model that maps technological capabilities to urban needs, this chapter proposes a suite of AI-driven urban solutions designed to establish a robust feedback loop between technology and demand. The distinguishing characteristics of AI 2.0—such as big da

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Al-Janabi, Samaher, and Zahraa Al-Barmani. "Intelligent Multi-level Analytics Approach to Predict Water Quality Index." In Hybrid Intelligent Systems. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-27409-1_7.

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Actes de conférences sur le sujet "Hybrid Analytical Intelligence"

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Talwalkar, Karan R., Kshitij Navale, Aditya Ashok, and Anindita Khade. "Design and Analytical Performance of a Hybrid Model Using Deep Learning Techniques for the Detection of Deepfake Videos." In 2024 International Conference on Artificial Intelligence and Quantum Computation-Based Sensor Application (ICAIQSA). IEEE, 2024. https://doi.org/10.1109/icaiqsa64000.2024.10882277.

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Sreeja, S. P., D. Sreenivasulu, Alok Jain, R. Akhilesh Reddy, Fatimah Dhari Jabbar, and V. Keerthi. "Advanced Hybrid Intelligence Framework for Scalable and Robust Big Data Analytics." In 2024 7th International Conference on Contemporary Computing and Informatics (IC3I). IEEE, 2024. https://doi.org/10.1109/ic3i61595.2024.10828582.

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Almarzooqi, Hamda A., and Anwar Jarndal. "Hybrid Neural Networks-Analytical Temperature-Dependent Electrothermal Model for GaN Transistors." In 2024 International Conference on Modeling, Simulation & Intelligent Computing (MoSICom). IEEE, 2024. https://doi.org/10.1109/mosicom63082.2024.10880944.

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Ma, Jiteng, Weimin Lv, Huiqi Xu, Xinyue Zhang, and Yanan He. "Domain-Specific Hybrid Normalization for Intelligent Fault Diagnosis." In 2024 International Conference on Sensing, Measurement & Data Analytics in the era of Artificial Intelligence (ICSMD). IEEE, 2024. https://doi.org/10.1109/icsmd64214.2024.10920615.

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Raman, Ramakrishnan, Vikram Kumar, Biju G. Pillai, Apurv Verma, Shailesh Rastogi, and R. Meenakshi. "Dynamic Hybrid Approaches for Decomposition-Based Multi-Objective Reinforcement Learning with a Taxonomy and Analytical Framework." In 2024 Asian Conference on Intelligent Technologies (ACOIT). IEEE, 2024. https://doi.org/10.1109/acoit62457.2024.10939067.

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Shi, Wei. "Control Model of Mechatronics Technology Based on Hybrid Particle Swarm Optimization." In 2024 3rd International Conference on Data Analytics, Computing and Artificial Intelligence (ICDACAI). IEEE, 2024. https://doi.org/10.1109/icdacai65086.2024.00054.

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Safa, Rieva Putri, and Raymond Sunardi Oetama. "Hybrid LSTM Model for Predicting Indonesian Telecommunication Companies Stock Price." In 2024 International Conference on Artificial Intelligence, Blockchain, Cloud Computing, and Data Analytics (ICoABCD). IEEE, 2024. http://dx.doi.org/10.1109/icoabcd63526.2024.10704303.

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Wei, Yuyang, Wenying Tao, Haoran Zhang, and Dianbin Kou. "Research on Cargo Volume Forecasting Based on the ARIMA-LSTM Hybrid Model." In 2024 3rd International Conference on Data Analytics, Computing and Artificial Intelligence (ICDACAI). IEEE, 2024. https://doi.org/10.1109/icdacai65086.2024.00169.

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Zhang, Changyu, Yamei Bai, and Lei Zhang. "Research on Electrical Engineering Network Teaching System Based on Hybrid Virtualization Technology." In 2024 3rd International Conference on Data Analytics, Computing and Artificial Intelligence (ICDACAI). IEEE, 2024. https://doi.org/10.1109/icdacai65086.2024.00176.

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Xinqi, Yang, Dai Zhiyuan, Yan Mingxuan, Jiang Yuyang, Liu Zhenyu, and Tao Zhi. "Enhancement of Photoacoustic Microscopy Images by Hybrid Activations and Half Instance Normalization." In 2024 International Conference on Sensing, Measurement & Data Analytics in the era of Artificial Intelligence (ICSMD). IEEE, 2024. https://doi.org/10.1109/icsmd64214.2024.10920495.

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Rapports d'organisations sur le sujet "Hybrid Analytical Intelligence"

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Perdigão, Rui A. P. Earth System Dynamic Intelligence with Quantum Technologies: Seeing the “Invisible”, Predicting the “Unpredictable” in a Critically Changing World. Meteoceanics, 2021. http://dx.doi.org/10.46337/211028.

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We hereby embark on a frontier journey articulating two of our flagship programs – “Earth System Dynamic Intelligence” and “Quantum Information Technologies in the Earth Sciences” – to take the pulse of our planet and discern its manifold complexity in a critically changing world. Going beyond the traditional stochastic-dynamic, information-theoretic, artificial intelligence, mechanistic and hybrid approaches to information and complexity, the underlying fundamental science ignites disruptive developments empowering complex problem solving across frontier natural, social and technical geoscien

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