Статті в журналах: "Intelligent model"

1

LIAO, Yunyan, Qing HUANG, Changjing WANG, Zhengkang ZUO, and Jiaxing LU. "Course Intelligent Brain Model Based on Crowd Intelligence." Wuhan University Journal of Natural Sciences 27, no. 4 (August 2022): 331–40. http://dx.doi.org/10.1051/wujns/2022274331.

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The development of artificial intelligence in education promotes the reform of teaching methods in the direction of intelligence and individuation. In this paper, the programming course is taken as an example to propose a curriculum intelligent brain model for open source swarm intelligence based on knowledge graph, and the bootstrapping framework is introduced to try to make the intelligent brain track the frontier like human beings and study several courses vertically. It studies the knowledge of subgraphs fusion of open-source software resources and domain semantics as well as the mining method of potential relationship, so that the intelligent brain can digest knowledge like human, and get through the course horizontally. Finally, knowledge discovery and natural representation based on knowledge graph enable intelligent brain to discover knowledge and solve problems just like human. This study provides new ideas, strategies, and application paths for the construction of knowledge graph based on big data and the integration of heterogeneous knowledge graph.

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2

Korovin, I. S., and M. G. Tkachenko. "Intelligent Oilfield Model." Procedia Computer Science 101 (2016): 300–303. http://dx.doi.org/10.1016/j.procs.2016.11.035.

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3

Zhao, Min, Zhenbo Ning, Baicun Wang, Chen Peng, Xingyu Li, and Sihan Huang. "Understanding the Evolution and Applications of Intelligent Systems via a Tri-X Intelligence (TI) Model." Processes 9, no. 6 (June 21, 2021): 1080. http://dx.doi.org/10.3390/pr9061080.

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The evolution and application of intelligence have been discussed from perspectives of life, control theory and artificial intelligence. However, there has been no consensus on understanding the evolution of intelligence. In this study, we propose a Tri-X Intelligence (TI) model, aimed at providing a comprehensive perspective to understand complex intelligence and the implementation of intelligent systems. In this work, the essence and evolution of intelligent systems (or system intelligentization) are analyzed and discussed from multiple perspectives and at different stages (Type I, Type II and Type III), based on a Tri-X Intelligence model. Elemental intelligence based on scientific effects (e.g., conscious humans, cyber entities and physical objects) is at the primitive level of intelligence (Type I). Integrated intelligence formed by two-element integration (e.g., human-cyber systems and cyber-physical systems) is at the normal level of intelligence (Type II). Complex intelligence formed by ternary-interaction (e.g., a human-cyber-physical system) is at the dynamic level of intelligence (Type III). Representative cases are analyzed to deepen the understanding of intelligent systems and their future implementation, such as in intelligent manufacturing. This work provides a systematic scheme, and technical supports, to understand and develop intelligent systems.

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4

He, Lin, Dongliang Yuan, Lianwei Ren, Ming Huang, Wenyu Zhang, and Jie Tan. "Evaluation Model Research of Coal Mine Intelligent Construction Based on FDEMATEL-ANP." Sustainability 15, no. 3 (January 25, 2023): 2238. http://dx.doi.org/10.3390/su15032238.

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To improve intelligent construction standard systems in coal mines, we must promote the high-quality development of the coal mining industry. The current intelligent construction of coal mines is inefficient. Considering the complexity and diversity of coal mine intelligent construction index factors, this paper proposes an intelligent coal mine construction evaluation model that integrates the fuzzy decision-making trial and evaluation laboratory (FDEMATEL) and the analytical network process (ANP). Firstly, the evaluation index system is established based on the intelligent construction of coal mines. Secondly, the FDEMATEL is applied to deal with the fuzziness in the evaluation process and determine the influence relationship between the evaluation indexes of coal mine intelligent construction to draw the ANP network structure diagram. Finally, super decision software is used to calculate the weight of coal mine intelligent construction evaluation indexes, and then obtain the combination weight and correlation degree of each evaluation index. By applying the evaluation model to conduct a comprehensive evaluation of coal mine intelligent construction, the results show that there is a significant correlation between the indexes affecting the intelligent construction of coal mines. Basic platform intelligence and safety monitoring intelligence are the two most important aspects of intelligent coal mine construction. Database construction, mobile internet construction, big data support, and model algorithm support are the key indexes affecting the intelligent construction of coal mines.

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Lv, Chengshuang, Jiaojiao Xu, and Caihui Wang. "Intelligent Strategies to Improve Food Safety Supervision Model." International Journal of Education and Humanities 1, no. 1 (December 15, 2021): 21–27. http://dx.doi.org/10.54097/ijeh.v1i1.197.

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Intelligent supervision effectively deals with food safety problems from four aspects: concept, subject, activity and object. This paper makes a qualitative analysis on the current situation of intelligent supervision of food safety in Beijing, Tianjin and Hebei, compares and studies the intelligent supervision modes of food safety in three coastal areas in eastern China, constructs the analysis framework of intelligent supervision of food safety, and improves the intelligent supervision mode of food safety in Beijing, Tianjin and Hebei. By studying the policy path of intelligent supervision of food safety, extract the three-stage three source stream model of supervision mode from standard cultivation, informatization to standard unification and intelligence, to better promote the intelligent supervision mode in the country. For the challenges still faced by food safety supervision, it is proposed to improve the top-level design and strengthen the intelligent supervision mechanism of cross regional coordination; Promote the cooperation and sharing of data resources and optimize the cross regional risk early warning mechanism; Consolidate the rural digital foundation and realize the integration mechanism of urban and rural food safety supervision.

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Liu, Runnan, Guangze Liu, Pengfei He, and Xingzhi Lin. "Research on artificial intelligence safety prediction and intervention model based on ship driving habits." MATEC Web of Conferences 355 (2022): 03032. http://dx.doi.org/10.1051/matecconf/202235503032.

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Based on the analysis of the causes of ship accidents, the development prospect and development direction of ship intelligent safe driving, the artificial intelligence safety prediction and intervention model is put forward. This model solves the problem of ship intelligent safety prediction by using intelligent analysis technology and network technology, and promotes the development of ship intelligence and ship safety navigation technology. Additionally, it expands the channels of obtaining information, connects the ship's mechanical and electrical equipment, collects, stores and analyzes the data reasonably, and constructs the intelligent analysis and processing platform of ship small-world data processing to implement intelligent intervention. What is impressive is that it makes ship navigation safer, more economical, more reasonable and optimized, and accelerates the development of ship artificial intelligence safe navigation.

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7

Li, Jing. "Construction and Model Realization of Financial Intelligence System Based on Multisource Information Feature Mining." Computational Intelligence and Neuroscience 2022 (July 4, 2022): 1–13. http://dx.doi.org/10.1155/2022/9363023.

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Multisource information mining systems and related business intelligence technology are currently a hot topic of research. However, the current commercial applications and applications are not ideal in terms of application. Because there is still much work to be done before decision support, it is best to transition to them only financially. This paper examines the multisource part of the information used in mining and introduces research hotspots in the fields of accounting informatization, the development status of intelligent financial analysis software, the research and application status of data warehouse, data mining, and decision support systems. This paper examines the specific composition and content of a financial information system using information mining to lay a solid foundation. Financial intelligent analysis, financial intelligent monitoring, financial intelligent decision-making, and financial intelligent early warning are the four parts of the financial intelligent system. It then examined the structure and processing of the financial intelligence system and proposed a financial intelligence system operation strategy. Financial intelligence low-risk integrated implementation strategies and ideal financial intelligence models, according to the current state of research and practical applications. According to the findings, the overall discrimination accuracy of the financial information system based on mining multisource information features is up to 95%, which is 42% higher than the traditional model. The development and use of financial information benefit from the realization and exploration of the financial intelligence system model.

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8

Tian, Yu, and Yonghong Zhang. "Evaluation of Accounting Data of Water Company Based on Combination Model." Scientific Programming 2022 (April 11, 2022): 1–9. http://dx.doi.org/10.1155/2022/3373420.

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Driven by the dual effects of artificial intelligence and accounting transformation, it has become one of the research hotspots of accounting intelligence in China to replace accountants with computers to make professional judgments and automatically evaluate accounting. On the basis of summarizing and analyzing the research status in the field of intelligent accounting, the realization path of intelligent accounting in water companies is put forward in this paper. By introducing the improved Apriori learning algorithm based on Boolean mapping matrix, intelligent data mining is carried out for evaluation of water accounting. With the help of the improved attribute inductive learning algorithm, the corresponding relationship between the original water consumption attribute and the water right transaction is mined and output. In addition, with the help of forward reasoning in inference engine technology, the computer intelligent data evaluation function is realized. Finally, the functional architecture of accounting system of the water company is designed, which provides reference for the development and application of intelligent accounting system, and explores a new path for the integration of accounting and intelligent algorithms.

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9

Majstorović, Vidosav. "Application of Industry 4.0 model in Oil and Gas companies." Journal of Engineering Management and Competitiveness 12, no. 1 (2022): 77–84. http://dx.doi.org/10.5937/jemc2201077m.

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Although the concept of Industry 4.0 was defined a decade ago, experts have only been talking about the "Oil and Gas 4.0" model in the last few years. Experts in this industry agree that the "Oil and Gas 4.0" model in use, based on the digitalization and intelligence of the oil and gas industry, can bring huge benefits to the company. However, the "Oil and Gas 4.0" model is still in its infancy, but applications in areas such as big data (BDA), industrial Internet of Things (IIoT), or analysis of typical oil and gas industry chain application scenarios through examples, such as an intelligent oil field, an intelligent pipeline, and an intelligent refinery, make today's challenges real. So the essence of the "Oil and Gas 4.0" model is a data-driven intelligence system based on high digitization. This paper provides an overview of the state and development of the Industry 4.0 concept in the Oil and Gas Industry.

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10

Liu, Zhenghao, and Xi Zeng. "Hybrid Intelligence in Big Data Environment: Concepts, Architectures, and Applications of Intelligent Service." Data and Information Management 5, no. 2 (January 5, 2021): 262–76. http://dx.doi.org/10.2478/dim-2020-0051.

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Abstract Based on the emerging concept of “Hybrid Intelligence,” this paper aims to explore a new model of human–computer interaction, and deeply research on its development and application of Intelligent Service in the big data environment. It systematically explores the related academic concepts of hybrid intelligence, and establishes its architecture model. The development of hybrid intelligence is faced with cognitive differences, system fragmentation, human–machine digital divide, and other issues. Strengthening the interaction between cognition and perception can be the key to break through the bottleneck. The intelligent service system based on the hybrid intelligent architecture takes knowledge fusion as the core, and “cloud intelligent brain” is making it possible for the human–computer symbiosis driven by hybrid intelligence. The proposed advanced human–computer interaction mode constructs a hybrid intelligent architecture model, enriches the concept system of human–machine hybrid intelligence, and provides a new landing scheme for intelligent services based on complex scenes in the big data environment.

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11

Kostenko, K. I. "Core Invariants of the Mathematical Model of an Intelligent System." Programmnaya Ingeneria 12, no. 3 (May 19, 2021): 157–68. http://dx.doi.org/10.17587/prin.12.157-168.

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A holistic description of a universal mathematical model for the concept of an intelligent system is given. It is based on formalized invariants associated with the processes of creating and applying such systems. The core of the model is formed by consistent descriptions for sections of knowledge formalisms, components of multidimensional architecture and knowledge flows processes within it, as well as cybernetic hierarchical multi agents systems that control the intelligent systems subjective existence. The fundamental invariants of the knowledge presentation and processing are directly implemented by these main sections basic elements. Invariants form unified set of intelligent systems general attributes. This set allows carrying out comprehensive formal modelling of the intelligence. These invariants are associated with knowledge aspects. They are developed and used at knowledge areas that deal with exploring the memory structural organization and thinking processes models. The tools for transforming the proposed abstract model into the models of specific intelligent systems are morphisms of homomorphic expansion. These morphisms concretize the content of the main structural and functional elements of the intelligent system fundamental model. At the same time, the varieties of entities implemented by model elements are narrowed to the families of objects that make up applied intelligent systems. These systems inherit the properties of fundamental model common elements. Intermediate models of the processes of converting the original model into applied ones allow studying these models properties by mathematical tools. Intermediate models form the basis for the subsequent development of the technology of creating and applying multilevel intelligent systems.

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12

Mahmudova, Shafagat. "Development of a Conceptual Model for Intelligent Software System Designing." Review of Information Engineering and Applications 9, no. 1 (April 18, 2022): 12–22. http://dx.doi.org/10.18488/79.v9i1.2967.

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This article provides information on the design of intelligent software systems. An intelligent software system refers to any software using artificial intelligence to analyze and interpret data or to communicate with systems and people. The article substantiates the relevance of the issue and highlights existing problems. The following factors are taken into consideration when assessing the problems of intelligent software system designing: easy data collection, low cost of developing intelligent systems, availability of experts and necessary resources (computers, program developers, software, etc.). The article also reports of related studies and identifies application areas. A conceptual model is developed for the design of intelligent software systems. The stages, components, directions, etc. indicated in the conceptual model for the design of intelligent software systems are studied and the characteristics of each are determined. Some examples of design types by the fields of activity are identified. The developed model can be used in the design of intelligent software systems related to any instrumental programming.

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13

Zhang, Mo, and Hai Shen. "Biological Communication Dynamic Model Research." Applied Mechanics and Materials 556-562 (May 2014): 4975–78. http://dx.doi.org/10.4028/www.scientific.net/amm.556-562.4975.

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Biological communication behavior is in everywhere, all over the nature, biological system and human society. In simple terms, Swarm intelligence is emerging though information communication and collaboration among some dispersed and simple individuals. Inspired by biological communication behavior, aimed at understanding swarm system collective dynamics behavior, and from the point of system cybernetics, this paper study the relevant biological communication dynamic model, such as the symbiotic model, attractive-repulsive model, external effect model and the multi-population coevolution model and so on. Also introduce the rules of these models, which provide theoretical basis for designing intelligent swarm intelligent system.

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14

MINDIZ, Emine. "Taking the Concept of Peculium as a Model for Determining the Legal Status of Robots with Artificial Intelligence." Ankara Üniversitesi Hukuk Fakültesi Dergisi 71, no. 3 (October 19, 2022): 937–70. http://dx.doi.org/10.33629/auhfd.1133837.

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Modern technology calls for a legal framework for the legal integrationof highly developed robots (autonomous robots-artificially intelligent robots)into our society. Because as a result of technological developments,artificially intelligent robots are used daily in many industries and byindividuals more and more. Since there is no special legal status provided forartificially intelligent robots, it has become a necessity to regulate legalsystems according to developments in artificial intelligence technology. Howthe legal status of this robots should be regulated is one of the mostdiscussed topics in scientific studies on the subject. One of the views putforward in the doctrine on this subject is that artificially intelligent robots areaccepted as electronic persons. However, granting legal personhood(electronic personhood) to robots for determining rights and responsibilitiesof these entities could cause some problems. Get the advantage of theinstitution of slavery while determining the legal status of artificiallyintelligent robots is another view put forward on this issue. In this respect,legal status of Roman slaves and specially the concept of peculium could bean alternative legal remedy.

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15

Derbel, Oussama, Tamás Péter, Hossni Zebiri, Benjamin Mourllion, and Michel Basset. "Modified Intelligent Driver Model." Periodica Polytechnica Transportation Engineering 40, no. 2 (2012): 53. http://dx.doi.org/10.3311/pp.tr.2012-2.02.

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16

Schleiffer, Ralf. "An intelligent agent model." European Journal of Operational Research 166, no. 3 (November 2005): 666–93. http://dx.doi.org/10.1016/j.ejor.2004.03.039.

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17

Rudakova, G. M., S. L. Gladkov, and O. V. Korchevskaya. "Intelligent data model concepts." Journal of Physics: Conference Series 1399 (December 2019): 033080. http://dx.doi.org/10.1088/1742-6596/1399/3/033080.

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18

Zeng, Rui, and Ying Yan Wang. "A Personalized Collaborative Learning Model Base on ACO Clustering." Applied Mechanics and Materials 135-136 (October 2011): 111–16. http://dx.doi.org/10.4028/www.scientific.net/amm.135-136.111.

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At present, the web-based collaborative learning is the main form of long-distance learning and it has been widely used in the distance learning domain. However, the main body-intelligence degree of the existing Web learning system is low; the existing system lacks to the support of the personal study, which has hindered the individual skill of the users. According to the question that exists in the collaborative Learning, I constructed the intelligent agent model of collaborative Learning which is composed of main control program, student proxy, teaching proxy and the information proxy based on the intelligent agent technology which belongs to the domain of Artificial Intelligence and I discussed emphatically how to effectively realize the personal study by using the machine learning and the data mining method. It can cause the web-based cooperative learning developing along the direction of intelligent and personal

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19

Tian, Xue Yong, Tian Qing Chang, Shao Hua Shi, Lei Zhang, and Yang Han. "Modeling of Test Resource Based on Multi-Agent and its Application in Intelligent Virtual Instrument." Advanced Materials Research 139-141 (October 2010): 1973–76. http://dx.doi.org/10.4028/www.scientific.net/amr.139-141.1973.

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Because of the poor reconfigurability of the existing test resource models and the faultiness of the intelligent modeling methods in automatic test system, the modeling method based on Multi-Agent was studied. By analyzing the characters of test resources, the test resource models were classified as device model, adapter model and configuration model. The typical test resource model based on Multi-Agent with three layers and five agents was built. The structure and function of system management agent, model reconfiguration agent, function management agent, channel control agent and function realization agent in the model were analyzed. Then its application in Intelligent Virtual Instrument was introduced. This model based on Multi-Agent has good reconfigurability and intelligence, and it can be used to build the general-purpose and intelligent automatic test system.

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20

Yang, Jianjun, Shanshan Xing, Yimeng Chen, Ruizhi Qiu, Chunrong Hua, and Dawei Dong. "An Evaluation Model for the Comfort of Vehicle Intelligent Cockpits Based on Passenger Experience." Sustainability 14, no. 11 (June 2, 2022): 6827. http://dx.doi.org/10.3390/su14116827.

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With the development of intelligence and network connectivity, the development of the automotive industry is also moving toward intelligent systems. For passengers, the utility of intelligence is to achieve more convenience and comfort. The intelligent cockpit is the place where passengers directly interact with the car, which directly affects the experience of passengers in the car. For the intelligent cockpits that have emerged in recent years, a reasonable and accurate comfort evaluation model is urgently needed. Therefore, in this article, from the passenger’s perspective, a subjective evaluation experiment was set up to collect data on four important indicators affecting the comfort of the intelligent cockpit: sound, light, heat, and human–computer interaction. The subjective evaluation weights were derived from a questionnaire, and the entropy weighting method was used to obtain the objective weights. Finally, the two weights were combined using the idea of game theory combination assignment to get the final accurate weights. Using the idea of penalty type substitution, the four index models were then synthesized to get the final evaluation model. The feasibility of the model was verified when measuring the car cockpit. The feasibility of the method means it can evaluate the comfort level of an intelligent cockpit more reasonably, facilitate the enhancement and improvement of the model, and promote the development of the model to achieve maximum passenger comfort.

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21

Fardinpour, Ali, Mir Mohsen Pedram, and Martha Burkle. "Intelligent Learning Management Systems." International Journal of Distance Education Technologies 12, no. 4 (October 2014): 19–31. http://dx.doi.org/10.4018/ijdet.2014100102.

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Virtual Learning Environments have been the center of attention in the last few decades and help educators tremendously with providing students with educational resources. Since artificial intelligence was used for educational proposes, learning management system developers showed much interest in making their products smarter and more intelligent. Nevertheless, the questions of what an intelligent learning management system (ILSM) is and which tools and features are needed to make such system intelligent, are not clearly answered, therefore educational institutes do not have a proper tool to decide upon the degree of intelligence they need for their LMSs. This paper proposes a prevalent, thorough definition of “Intelligent Learning Management Systems”, and the design of a fuzzy model to measure the intelligence of these systems. In order to devise a comprehensive definition of an Intelligent Learning Management System, experts from around the world were consulted. Following that, different proposed Intelligent Learning Management Systems were studied, and forty-one features and tools were found and analyzed. After the analysis, experts' opinions were taken into account to rank these features. The paper proposes thirteen most significant features and tools as criteria to be used in fuzzy analytic hierarchy process (AHP) as a fuzzy model to measure the intelligence of Learning Management System.

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22

Guo, Wang, Hui Shu, Yeming Gu, Yuyao Huang, Hao Zhao, and Yang Li. "A Novel Virus Capable of Intelligent Program Infection through Software Framework Function Recognition." Electronics 12, no. 2 (January 16, 2023): 460. http://dx.doi.org/10.3390/electronics12020460.

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Viruses are one of the main threats to the security of today’s cyberspace. With the continuous development of virus and artificial intelligence technologies in recent years, the intelligentization of virus technology has become a trend. It is of urgent significance to study and combat intelligent viruses. In this paper, we design a new type of confirmatory virus from the attacker’s perspective that can intelligently infect software frameworks. We aim for structural software as the target and use BCSD (binary code similarity detection) to identify the framework. By incorporating a software framework functional structure recognition model in the virus, the virus is enabled to intelligently recognize software framework functions in executable files. This paper evaluates the BCSD model that is suitable for a virus to carry and constructs a lightweight BCSD model with a knowledge distillation technique. This research proposes a software framework functional structure recognition algorithm, which effectively reduces the recognition precision’s dependence on the BCSD model. Finally, this study discusses the next researching direction of intelligent viruses. This paper aims to provide a reference for the research of detection technology for possible intelligent viruses. Consequently, focused and effective defense strategies could be proposed and the technical system of malware detection could be reinforced.

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23

Dai, Dan Dan. "Artificial Intelligence Technology Assisted Music Teaching Design." Scientific Programming 2021 (December 21, 2021): 1–10. http://dx.doi.org/10.1155/2021/9141339.

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With the continuous improvement of the global economic level and scientific level, information technology has penetrated into all fields of people’s life. Today, the strategy of vigorously promoting educational modernization has created conditions for intelligent music teaching and promoted the in-depth application of artificial intelligence technology in education. Intelligent instructional design supported by artificial intelligence technology is the deep integration of information technology and music teaching. Through the intelligent perception technology, learning analysis technology, and emotional computing technology of artificial intelligence, an intelligent music teaching model is established. The online learning and education platform based on big data intelligence provides teachers with rich teaching methods, provides personalized evaluation and adaptive learning services for students’ learning, and helps improve the efficiency of music teaching. The traditional teaching design model cannot effectively guide the intelligent music teaching and cannot meet the needs of students’ development. Therefore, on the basis of previous studies, the author studies the intelligent teaching design supported by artificial intelligence technology. This study uses new generation information technologies such as big data, Internet of things, mobile Internet, and artificial intelligence to build a complete set of scientific intelligent music teaching design model. Wisdom teaching provides a reference for the whole process before, during, and after class, helps guide teachers to better carry out wisdom teaching, helps students explore cooperative and autonomous learning, and promotes the wisdom transformation of teaching methods and learning methods to a certain extent. Music classroom teaching has become more targeted and effective. Therefore, it is of great significance to cultivate intelligent music talents.

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Wei, YongHui, KeYu Zhao, XueQiang Lv, JianZhou Feng, HaiJu Hu, Tuyatsetseg Badarch, and ZeYu Zhao. "Research on Intelligent Embedded Fan System Based on YOLOv2 Lightweight Algorithm." Computational Intelligence and Neuroscience 2022 (July 22, 2022): 1–9. http://dx.doi.org/10.1155/2022/3484268.

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With the development of artificial intelligence, the application of intelligent algorithms to low-power embedded chips has become a new research topic today. Based on this, this study optimizes the YOLOv2 algorithm by tailoring and successfully deploys it on the K210 chip to train the face object detection algorithm model separately. The intelligent fan with YOLOv2 model deployed in K210 chip can detect the target of the character and obtain the position and size of the character in the machine coordinates. Based on the obtained information of character coordinate position and size, the fan's turning Angle and the size of air supply are intelligently perceived. The experimental results show that the intelligent fan design method proposed here is a new embedded chip intelligent method of cutting and improving the YOLOv2 algorithm. It innovatively designed solo tracking, crowd tracking, and intelligent ranging algorithms, which perform well in human perception of solo tracking and crowd tracking and automatic air volume adjustment, improve the accuracy of air delivery and user comfort, and also provide good theoretical and practical support for the combination of AI and embedded in other fields.

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Hoe, Ho Kok, Kanesan Muthusamy, and Harikrishnan Kanthen. "An Intelligent Process Model for Manufacturing System Optimization." Advanced Materials Research 383-390 (November 2011): 6674–78. http://dx.doi.org/10.4028/www.scientific.net/amr.383-390.6674.

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The paper aims to develop an intelligent modeling system using Microsoft Excel spreadsheet interface through mathematical language, mathematical reasoning and algorithms flow chart technique for manufacturing system optimization without human involvement. The paper begins to search for a mathematical theorem which is arithmetic series to represent a dynamic manufacturing system in a production floor using production time variable through numerical analysis and is validated using software simulation. The mathematical theorem is modeled with Industrial Engineering (IE) variables into spreadsheet to perform intelligent decision making. The model sets inventory target variable to be achieved with automated computation through the data input from users. Manual analysis from human can be transposed to mathematical language in order automate the system intelligently. The building of intelligent modeling system into spreadsheet using mathematical language sets a new platform for researchers to promote the next generation of modeling technique in the manufacturing field.

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Yu, Yan, and Jian Hua Wang. "Research on Network Examination System Model Based on Multi-AGENT." Advanced Materials Research 566 (September 2012): 685–90. http://dx.doi.org/10.4028/www.scientific.net/amr.566.685.

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With the development of artificial intelligence, Multi-agent technology is applied more and more in reality. In line with multi-user intelligent network examination test system, this paper proposes multi-agent-based general examination system model constituted by multiple mutually independent but collaborated AGENTs. In addition to fulfill their respective responsibilities, every single sub-Agent communicates among each other to gain information and complete missions in a collaborative form. Also, dedicated data mining AGENT is deployed in the system to conduct intelligent analysis and processing on various data, thereby providing decision support for teachers’ teaching and student’s study duties. And this paper presents a new clue for establishing intelligent network examination system under distributed environment.

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Liu, Hai Ying. "Control System of Image Synthesis Based on Cluster Mathematical Model of K-Means Intelligent Computer." Applied Mechanics and Materials 543-547 (March 2014): 2431–34. http://dx.doi.org/10.4028/www.scientific.net/amm.543-547.2431.

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On the basis of computer automatic control theory of artificial intelligence, we use Kmeans clustering algorithm to establish mathematical model of automatic art synthesis for computer painting, and realize the computer artificial intelligence painting synthesis by using MATLAB software. In the first part we introduce the intelligent control system of computer drawing in detail, and do decomposition and combination on the frame number by using the computer intelligent drawing cell. In the second part we establish the intelligent clustering model of Kmeans algorithm, and introduce the model painting synthesis. In order to verify the availability and reliability of the model designed in this paper, we design simulation experiment of MATLAB drawing synthesis, and obtain the art synthesis of clothing abstract drawing by calculation. It provides the theory reference for the research on computer artificial intelligence control technology

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28

Fan, Rui, and Xiao Hui Liu. "Dynamic Modeling of Intelligent Connector." Advanced Materials Research 108-111 (May 2010): 313–18. http://dx.doi.org/10.4028/www.scientific.net/amr.108-111.313.

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To construct autonomous, dynamic evolvement software entity, and dynamically assemble them under the Internet environment for the complex software system, a novel intelligent software model is critical. Although there is significant literature on implementation of enterprise software systems, there are fewer contributions that give rigorous formal analyzing. In this paper, we present formal model of intelligent connector for constructing enterprise intelligent applications. As a core of the enterprise intelligence component, our model is presented at different levels of abstraction and formalism by π-calculus, and the characters of dynamic rebuilding, intelligent controlling business chains are formally analyzed. A case is given to illustrate its dynamic properties.

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Ying-Ming Shi, Ying-Ming Shi. "Improved Algorithm of Intelligent Decision Making for Precise Application of Nitrogen Fertilizer to Melon Based on Artificial Intelligence." 電腦學刊 33, no. 5 (October 2022): 185–95. http://dx.doi.org/10.53106/199115992022103305016.

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<p>As agriculture enters the 4.0 era, the demand for intelligent and precise agricultural production is gradually increasing. However, the high cost of agricultural data collection, insufficient decision-making models and low level of intelligence are still the main obstacles to the improvement of land output rate and labor productivity in the process of agricultural production. In this paper, to address the long-standing problems of high cost of soil nitrogen content sampling, difficulty in acquiring soil nitrogen content and reduced accuracy of model long-term prediction during melon growth, a soil nitrogen content prediction model based on improved BP neural network combining a small amount of sampling and a comprehensive model is constructed to realize intelligent decision making of melon nitrogen fertilizer application.</p> <p> </p>

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Qin, Wei, and Qingna Lin. "Research on the Fusion Model of Professional Vocal Music Performance Voice Care and Artificial Intelligence Technology in Intelligent Medical Treatment." Wireless Communications and Mobile Computing 2022 (May 9, 2022): 1–7. http://dx.doi.org/10.1155/2022/2947554.

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Intelligent medical treatment is an important research field in today’s world. Artificial intelligence technology is the key factor to construct intelligent medical treatment. In the development of artificial intelligence technology, it is necessary to establish a scientific, systematic, and comprehensive system analysis model, inevitably with certain professional characteristics. At present, in the research of vocal health care in professional vocal music performance, the application of intelligent medical care and vocal health care in professional vocal music performance is studied. According to the DEMATEL-ISM research method, this paper constructs 4 internal and external factors and 16 influencing factors to build a comprehensive and systematic weight analysis model, which provides a theoretical and practical basis for the scientific construction of AI technology algorithms. The aim is to improve the value and research significance of intelligent medical artificial intelligence technology in professional vocal music performance sound care.

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Zhou, Dongdong, Ke Xu, Zhimin Lv, Jianhong Yang, Min Li, Fei He, and Gang Xu. "Intelligent Manufacturing Technology in the Steel Industry of China: A Review." Sensors 22, no. 21 (October 26, 2022): 8194. http://dx.doi.org/10.3390/s22218194.

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Intelligent manufacturing, defined as the integration of manufacturing with modern information technologies such as 5G, digitalization, networking, and intelligence, has grown in popularity as a means of boosting the productivity, intelligence, and flexibility of traditional manufacturing processes. The steel industry is a necessary support for modern life and economic development, and the Chinese steel industry’s capacity has expanded to roughly half of global production. However, the Chinese steel industry is now confronted with high labor costs, massive carbon emissions, a low level of intelligence, low production efficiency, and unstable quality control. Therefore, China’s steel industry has launched several large-scale intelligent manufacturing initiatives to improve production efficiency, product quality, manual labor intensity, and employee working conditions. Unfortunately, there is no comprehensive overview of intelligent manufacturing in China’s steel industry. We began this research by summarizing the construction goals and overall framework for intelligent manufacturing of the steel industry in China. Following that, we offered a brief review of intelligent manufacturing for China’s steel industry, as well as descriptions of two typical intelligent manufacturing models. Finally, some major technologies employed for intelligent production in China’s steel industry were introduced. This research not only helps to comprehend the development model, essential technologies, and construction techniques of intelligent manufacturing in China’s steel industry, but it also provides vital inspiration for the manufacturing industry’s digital and intelligence updates and quality improvement.

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Wang, Jian Hua, Yan Yu, and Jun Jie Guo. "The Study on the Multiple Agent-Based Independent and Collaborative Intelligent Tutoring System Model." Advanced Materials Research 846-847 (November 2013): 1885–88. http://dx.doi.org/10.4028/www.scientific.net/amr.846-847.1885.

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Over the years, the traditional computer-assisted teaching can not meet the needs of university teaching, the traditional teaching system software, most of the existence of low intelligence, lack of teaching strategies and other shortcomings.Multi-AGENT technology and intelligent tutoring systems is the current research focus in computer intelligence education. Integrating multi-Agent features and multi-Agent application theories in ITS, this paper proposes a multiple Agent-based intelligent network tutoring system design model, detailedly analyzes the functions of each layer in the system, and presents system database category design and system model features.

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Liang, Ting Ting, and Chun Qing Li. "Intelligent Science of Knowledge Retrieval System Model Based on Ontology." Applied Mechanics and Materials 707 (December 2014): 441–44. http://dx.doi.org/10.4028/www.scientific.net/amm.707.441.

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Compared with the traditional information retrieval, knowledge retrieval based on ontology has higher retrieval efficiency. In order to adequate arena for the effectiveness of knowledge,and intelligence to meet the users on the implicit and explicit knowledge retrieval demand, the author designed a system model of intelligent science based on ontology. Detailed analysis and elaboration of the three aspects: subject knowledge ontology construction, ontology knowledge retrieval, service based on intelligent. Provide methodological guidance and technical support to enrich the research contents in the field of knowledge retrieval.

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Hitz, Martin, Hannes Werthner, and Giorgio Guariso. "An intelligent simulation model generator." SIMULATION 53, no. 2 (August 1989): 57–66. http://dx.doi.org/10.1177/003754978905300204.

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35

Chaiyarak, Sakchai, Prachyanun Nilsook, and Panita Wannapiroon. "IVUL Model: An Intelligent Learning Development Process." International Journal of Emerging Technologies in Learning (iJET) 17, no. 14 (July 26, 2022): 39–51. http://dx.doi.org/10.3991/ijet.v17i14.31527.

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The purposes of this research study are to develop an intelligent virtual universal learning (IVUL) model and to evaluate its appropriateness. The study consisted of two phases. Phase 1 involved the development of the IVUL model for univer-sal learning. The conceptual frameworks and theories in the documents and re-search studies on universal design for learning, intelligent learning and virtual learning were studied by the researchers. All main components were then synthe-sised to design the IVUL model. This process can be divided into three main steps: engagement, representation, and action and expression. Each step has sub-steps: access, build and internalise. However, the details of these are dependent on the main steps. The second component is the intelligent learning process, an important process of the model that drives learners to automatically learn by themselves. Artificial intelligence is used as a crucial component that promotes and supports each learner to meet learning goals and objectives according to the universal learning model. The third component is the virtual learning process, which results in learning through computer environments and the Internet. Phase 2 involved an evaluation of the appropriateness of the IVUL model, with in-depth interviews with 20 experts in education and digital technologies. The appropriate-ness of the model was evaluated using the 5-point Likert scale. The findings show that the designed IVUL model can be used for learning development at the highest level.

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Sun, Yanfei, Feng Qiao, Wei Wang, Bin Xu, Jianming Zhu, Romany Fouad Mansour, and Jin Qi. "Dynamic Intelligent Supply-Demand Adaptation Model Towards Intelligent Cloud Manufacturing." Computers, Materials & Continua 72, no. 2 (2022): 2825–43. http://dx.doi.org/10.32604/cmc.2022.026574.

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WU, Hongxin. "Intelligent control based on intelligent characteristic model and its application." Science in China Series F 46, no. 3 (2003): 225. http://dx.doi.org/10.1360/03yf9019.

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Schlechtendahl, J., S. Braun, P. Schraml, E. Abele, U. Heisel, A. Verl, and A. Lechler. "Modellbasierte, energieoptimale Maschinensteuerung*/Model-based, energy-optimal production control - Reduction of energy consumption over multiple layers within the control hierarchy." wt Werkstattstechnik online 105, no. 06 (2015): 440–44. http://dx.doi.org/10.37544/1436-4980-2015-06-92.

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Der Einfluss moderner Werkzeugmaschinen auf die Umwelt basiert größtenteils auf deren Energieverbrauch im Produktivbetrieb. Um diesen Energieverbrauch zu senken, bietet sich der Einsatz von modellbasierten Strategien an. Für die Nutzung dieser Strategien in Werkzeugmaschinensteuerungen müssen modellbasierte Optimierer und Steuerungsinformationen zur intelligenten Energieverbrauchssteuerung verknüpft werden. In diesem Fachbeitrag wird ein Ansatz für eine intelligente Energieverbrauchssteuerung vorgestellt sowie anhand von Prozess- und Komponentenoptimierern validiert. Teil 1 des Fachbeitrags ist erschienen in der wt-Ausgabe 5-2015 auf den Seiten 324–328.   Modern machine tools mainly affect the environment by their energy consumption during operational life. Model-based strategies could be used for decreasing the energy consumption of machine tools. To enable the use of these strategies in machine controls, model-based optimizers and control information need to be connected to an intelligent energy controller. This paper introduces an approach to an intelligent energy controller for machine tools, validated by process and component optimizers.

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Pei, Zhi Li, Qing Hu Wang, Jie Lian, and Bin Wu. "A MSTP DNA Computing Model Based on Genetic Algorithm and Incompletion-Molecule Commixed Encoding Strategy." Applied Mechanics and Materials 411-414 (September 2013): 2056–61. http://dx.doi.org/10.4028/www.scientific.net/amm.411-414.2056.

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Artificial intelligence based on the genetic algorithm and DNA computing based on the biological intelligence is two kinds of important intelligent computing model, Graph theory and combinatorial optimization problem is a hotspot of research on intelligent computing. This paper designs a coding space optimized by using genetic algorithm, and by using DNA computing to solve Minimum Spanning Tree Problem calculation model. Because MSTP (Minimum Spanning Tree Problem) refer to Weight, IMCE (Incompletion-Molecule Commixed Encoding) is used in vertex, edges and weights encoding. The calculation process of the MSTP solution has been detailed described detailed.

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Imamverdiyev, Yadigar, and Babek Nabiyev. "CONCEPTUAL MODEL FOR THE INTELLIGENT NETWORK SECURITY MONITORING." Problems of Information Society 08, no. 1 (January 23, 2017): 70–77. http://dx.doi.org/10.25045/jpis.v08.i1.09.

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LIU, Lian. "Application and Research of Folk Music Composition Based on Artificial Intelligence Technology." Theory and Practice of Social Science 2, no. 2 (June 30, 2020): 35–41. http://dx.doi.org/10.6914/tpss.202006_2(2).0004.

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Music is one of the important forms of human emotion expression. Using artificial methods and technologies to allow the machine to quickly identify optical scores and real-time music sounds, through the inference and optimization of music emotion models, obtain human music emotion expression patterns, and actively complete human-machine collaboration with intelligent composition, and other related services. The development of multi-source perception of affective artificial intelligence has important research value and practical significance. This article mainly integrates multiple models of existing artificial intelligence models (typed music models, Markov chain models, genetic algorithm models, neural network models, etc.) to improve the rule knowledge to form a practical and effective hybrid model. Its innovation lies in combining formulas and matrix data combinations to intelligently compose non-note units (reproducing structures) in automatic composition, so as to achieve harmony, audibility and intelligence of music.

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Li, Caimin. "Implementation and Analysis of Intelligent Inquiry Teaching Model in Primary School English Teaching." Science Insights Education Frontiers 8, S1 (January 22, 2021): 4. http://dx.doi.org/10.15354/sief.21.s1.ab015.

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As a linguistic discipline, the critical point of teaching English is to cultivate students’ comprehensive language application ability in listening, speaking, reading, and writing. Moreover, the cultivation of ability requires authentic linguistic context. The intelligent learning environment can provide a more authentic English situation in the intelligent inquiry teaching model and help students’ better familiar with communication methods. What is more, it attaches great importance to students’ learning process, such as discovery, induction, and evaluation, as a result, to promote and develop students’ intelligence. Based on intelligent inquiry teaching mode research, this article chose the E-book Bag as the learning environment. It focused on its improvement and application in primary school English teaching.

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BUITEN, Miriam C. "Towards Intelligent Regulation of Artificial Intelligence." European Journal of Risk Regulation 10, no. 1 (March 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 the input data, the testing of the algorithm and the decision model. Any transparency requirement for algorithms should result in explanations of these biases that are both understandable for the prospective recipients, and technically feasible for producers. Before asking how much transparency the law should require from algorithms, we should therefore consider if the explanation that programmers could offer is useful in specific legal contexts.

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Lv, Zhi Jun, Qian Xiang, and Jian Guo Yang. "An Intelligent Decision Model for Spinning Process Optimization." Advanced Materials Research 538-541 (June 2012): 439–43. http://dx.doi.org/10.4028/www.scientific.net/amr.538-541.439.

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The yarn production is a complex industrial process, and the relation between the spinning variables and the yarn properties has not been established conclusively so far. In fact, the existing process cases which were recorded to ensure the ability to trace production steps can also be used to optimize the process itself. This paper presents a novel process decision model based on CBR and SVM hybird intelligence for optimization of large numbers of spnning parameters. The applied cases are demonstrated that the intelligent model to optimizing the spinning process is promising.

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Huang, Chun Yue, He Geng Wei, Tian Ming Li, and De Jin Yan. "Study on Intelligent Analysis of the Causes of SMT Solder Joint Defects Based on Fuzzy Neural Network." Advanced Materials Research 189-193 (February 2011): 3257–61. http://dx.doi.org/10.4028/www.scientific.net/amr.189-193.3257.

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By determining membership function of the input parameters and selecting defuzzification method, the evaluation model which can be used to intelligent analyzing the causes of SMT solder joint defects was set up. The fuzzy neural network was trained by using the output variables of the training samples from intelligent discrimination as the input variables of training samples of fuzzy neural network. The fuzzy neural network was tested by using the output variables of the testing samples from intelligent discrimination as the input variables of testing samples of fuzzy neural network. The results show that by using the evaluation model the cause of SMT solder joint defects can be analyzed intelligently and the results of intelligently analysis are reasonable, the evaluation model can be used practically.

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MO, Shancong, Zhijia XU, and Wenbin TANG. "Product information modeling for capturing design intent for computer-aided intelligent assembly modeling." Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University 40, no. 4 (August 2022): 892–900. http://dx.doi.org/10.1051/jnwpu/20224040892.

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Intelligent assembly is a bottleneck to be broken with urgency in the on-going revolution of manufacturing industry. However, computer-aided assembly modeling as an important supporting technology is still suffering from the problems of too many manual interventions and low-level intelligence. An intelligent assembly modeling technology was previously developed based on design intent (DI), however there lacks systematical and supportive product information model. Consequently, a novel product information model that can capture DI for computer-aided intelligent assembly modeling is established, based on the previously developed concept of interaction feature pair (IFP). The corresponding meta class model is also constructed utilizing the object-oriented technology. On this basis, the implementation process of the product information model, as well as algorithms supporting the process of computer-aided intelligent assembly modeling, is clarified, and the algorithms include IFP identification and intelligent part matching. Computer-aided intelligent assembly modeling prototype system based on the product information model, together with a case study, validated the feasibility of the proposed technology.

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Li, Xiaoguang. "The Construction of Intelligent English Teaching Model Based on Artificial Intelligence." International Journal of Emerging Technologies in Learning (iJET) 12, no. 12 (December 20, 2017): 35. http://dx.doi.org/10.3991/ijet.v12i12.7963.

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In order to build a modernized tool platform that can help students improve their English learning efficiency according to their mastery of knowledge and personality, this paper develops an online intelligent English learning system that uses Java and artificial intelligence language Prolog as the software system. This system is a creative reflection of the thoughts of expert system in artificial intelligence. Established on the Struts Spring Hibernate lightweight JavaEE framework, the system modules are coupled with each other in a much lower degree, which is convenient to future function extension. Combined with the idea of expert system in artificial intelligence, the system developed appropriate learning strategies to help students double the learning effect with half the effort; Finally, the system takes into account the forgetting curve of memory, on which basis the knowledge that has been learned will be tested periodically, intending to spare students’ efforts to do a sea of exercises and obtain better learning results.

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Yu, Ming, Qian Wan, Songling Tian, Yanyan Hou, Yimiao Wang, and Jian Zhao. "Equipment Identification and Localization Method Based on Improved YOLOv5s Model for Production Line." Sensors 22, no. 24 (December 19, 2022): 10011. http://dx.doi.org/10.3390/s222410011.

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Intelligent video surveillance based on artificial intelligence, image processing, and other advanced technologies is a hot topic of research in the upcoming era of Industry 5.0. Currently, low recognition accuracy and low location precision of devices in intelligent monitoring remain a problem in production lines. This paper proposes a production line device recognition and localization method based on an improved YOLOv5s model. The proposed method can achieve real-time detection and localization of production line equipment such as robotic arms and AGV carts by introducing CA attention module in YOLOv5s network model architecture, GSConv lightweight convolution method and Slim-Neck method in Neck layer, add Decoupled Head structure to the Detect layer. The experimental results show that the improved method achieves 93.6% Precision, 85.6% recall, and 91.8% mAP@0.5, and the Pascal VOC2007 public dataset test shows that the improved method effectively improves the recognition accuracy. The research results can substantially improve the intelligence level of production lines and provide an important reference for manufacturing industries to realize intelligent and digital transformation.

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Tang, Kai. "Research on the Construction of Personalized Active Information Service Model in Digital Library." Advanced Materials Research 753-755 (August 2013): 3071–74. http://dx.doi.org/10.4028/www.scientific.net/amr.753-755.3071.

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Based on study of users behaviors, interests, hobbies, professional fields and habits, personalized active information service in digital library is a kind of information service which takes the user's personalized needs as the center. Its key technologies includes user modeling technology, intelligent agent technology, ontology technology, Web data mining, personalized recommendation technology and information push technology etc. Based on the above technologies, this paper constructs a kind of multi-technology personalized active information service model, which can give full play to superiority of various technologies, and has the feature of intelligence. The model applies the technology of user modeling, ontology, intelligent agent, and draws on the general principle of personalized active information service, which is characterized by self-learning, self-renewal and other intelligent elements.

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Wang, Zhan. "Design of the Intelligent Recognition Model for English Translation Based on the BP Neural Algorithm." Security and Communication Networks 2022 (October 6, 2022): 1–12. http://dx.doi.org/10.1155/2022/3799061.

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With the development of modern intelligent recognition, many intelligent recognition translation tools have emerged. These translation tools mainly include machine learning, neural network, KNN, and other artificial intelligence technologies. These technologies have been applied to many fields. Among them, machine translation is the most important and widely used one. A large number of English translation technologies have appeared in this development era. However, the translation accuracy of intelligent recognition technology cannot be guaranteed. Under the background of this English translation environment, we design an intelligent recognition algorithm of English translation based on the BP neural algorithm to improve the rationality of English translation and analyze the intelligent recognition model of English translation. The following conclusions are drawn from the experimental comparison Four Methods of Translation. (1) Compared with some similar algorithms, machine translation based on the BP neural algorithm has many characteristics, such as convenience, which are very suitable for English translation. (2) The intelligent recognition model of English translation using the BP neural network makes the sentence flow higher, which can solve some problems in translation and achieve coherent translation in context. (3) The intelligent recognition model with the BP neural network as the core realizes a variety of permutations and combinations of different characteristics of complex English sentences, solves many poor English sentences, and significantly improves the accuracy of English translation.

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