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Prospects for multi-agent collaboration and gaming: challenge, technology, and application Perspective
Yu LIU, Zhi LI, Zhizhuo JIANG, You HE
Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 7, Pages 1002-1009 doi: 10.1631/FITEE.2200055
Keywords： 多智能体；博弈论；集体智能；强化学习；智能控制
The Electrically Controlled Flame Synthesis of Oxide Nanop article
Zhuang Qingping
Strategic Study of CAE 2007, Volume 9, Issue 2, Pages 74-78
For precise control of the nanophase powder characteristics, electrically assisted hydrocarbon flames using electrodes have shown quite effective, either by ion or electron attachment, so the coagulation rate of the particles is reduced, as unipolarly charged particles repel each other. Charged particles are also attracted towards electrodes, thus lowering the local particle concentration and therefore the collision rate. The flame structure, height, and temperature are also altered by the electric field, which can significantly influence the particle residence time at high temperatures and therefore affect particle growth or sintering and crystallinity. It was shown that field generated by the electrodes across the flame decreases the particle residence time in the high temperature region of the flame.
Keywords： gas combustion electrically controlled flame nanoparticle aggregates
Multi-Peptide Adsorption on Uncharged Solid Surfaces: A Coarse-Grained Simulation Study Research
Ruosang Qiu, Jie Xiao, Xiao Dong Chen
Engineering 2020, Volume 6, Issue 2, Pages 185-194 doi: 10.1016/j.eng.2018.12.012
On-aim control of protein adsorption onto a solid surface remains challenging due to the complex interactions involved in this process. Through computational simulation, it is possible to gain molecular-level mechanistic insight into the movement of proteins at the water-solid interface, which allows better prediction of protein behaviors in adsorption and fouling systems. In this work, a mesoscale coarse-grained simulation method was used to investigate the aggregation and adsorption processes of multiple 12-Ala hydrophobic peptides onto a gold surface. It was observed that around half (46.6%) of the 12-Ala peptide chains could form aggregates. 30.0% of the individual peptides were rapidly adsorbed onto the solid surface; after a crawling process on the surface, some of these (51.0%) merged into each other or merged with floating peptides to form adsorbed aggregates. The change in the solid-liquid interface due to peptide deposition has a potential influence on the further adsorption of single peptide chains and aggregates in the bulk water. Overall, the findings from this work help to reveal the mechanism of multi-peptide adsorption, and consequentially build a basis for the understanding of multi-protein adsorption onto a solid surface.
Keywords： Peptide chains Aggregates Adsorption Coarse-grained simulation
The Application of Multi-agent Based Distributed Intelligent Control in VAV Air Conditioning System
Zhang Hongwei,Wu Aiguo,Sheng Tao
Strategic Study of CAE 2006, Volume 8, Issue 7, Pages 58-62
A VAV system can be treated as a multi-agent system. In this paper, a multi-agent-based distributed intelligent control method is presented to solve the problem of concordance and decoupling in the VAV system. A simulation program of VAV system is set up for control analysis. Through a simulation, this control method has been proved to be satisfactory.
Keywords： VAV agent multi-agent system distributed intelligent control
Intelligent Products and Equipment Led by New-Generation Artificial Intelligence
Tan Jianrong, Liu Zhenyu, Xu Jinghua
Strategic Study of CAE 2018, Volume 20, Issue 4, Pages 35-43 doi: 10.15302/J-SSCAE-2018.04.007
Intelligent products and equipment is the value carrier, technological prerequisite and material base of intelligent manufacturing and service. The intelligent products and equipment refers to two dialectical aspects: on the one hand, commercialization of intelligent technology, turning intelligence technology into products, which is mainly reflected in the comprehensive application of the Internet of Things, big data, cloud computing, edge computing, machine learning, deep learning, security monitoring, automation control, computer technology, precision sensing technology, and GPS positioning technology; On the other hand, the intelligent products and equipment refers to the intellectualization of traditional products. The new-generation artificial intelligence endows traditional products with higher intelligence and injects strong vitality and developmental motivation into traditional products in the aspect of intelligent manufacturing equipment, intelligent production, and intelligent management. Based on extensive scientific surveys and current researches, and combined with the ten major fields of Made in China 2025 and macro policies such as the Three-Year Action Plan for Artificial Intelligence, twelve major equipment fields of intelligent products and equipment are formulated. Researches show that the new-generation intelligent products and equipment focuses on knowledge engineering and is prominently characterized by self-sensing, self-adaptation, self-learning, and self-decision-making. Ten key technologies will be prioritized in future.
Keywords： intelligent products and equipment knowledge engineering intelligent state sensing intelligent variation adaptation intelligent knowledge learning intelligent control decision
Jiang Changjun, Wang Junli
Strategic Study of CAE 2018, Volume 20, Issue 6, Pages 93-100 doi: 10.15302/J-SSCAE-2018.06.015
Artificial Intelligence (AI) aims to simulate information storage and processing mechanisms and other intelligent behaviors of a human brain, so that the machine has a certain level of intelligence. With the rapid development of the new generation of information technology, such as the Internet, big data, cloud computing, and deep learning, researches and applications of AI have made and are making important progresses. In this paper, the historical integration and evolution of computer science, control science, brain-inspired intelligence, human brain intelligence, and other disciplines or fields closely related to AI are analyzed in depth; then it is pointed out that the research results on the structure and functional mechanism of brain from neuroscience, brain science and cognitive science provide some important inspirations for the construction of an intelligent computing model. Moreover, the drives and developments of AI are discussed from the aspects of logic model and system, neuron network model, visual nerve hierarchy mechanism, etc. Finally, the development trend of AI is prospected from the following five aspects: the computational theory of the Internet, the integration of AI calculus and computation, the model and mechanism of brain-inspired intelligence, the impetus of AI to neuroscience, and the algorithm design of feedback computation and the energy level of the control system.
Keywords： artificial intelligence human brain intelligence brain-inspired intelligence intelligence development discipline evolution
Applications of artificial intelligence in intelligent manufacturing: a review Review
Bo-hu LI,Bao-cun HOU,Wen-tao YU,Xiao-bing LU,Chun-wei YANG
Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 1, Pages 86-96 doi: 10.1631/FITEE.1601885
Keywords： Artificial intelligence Intelligent manufacturing Intelligent manufacturing system
Toward Intelligent Machine Tool Article
Jihong Chen, Pengcheng Hu, Huicheng Zhou, Jianzhong Yang, Jiejun Xie, Yakun Jiang, Zhiqiang Gao, Chenglei Zhang
Engineering 2019, Volume 5, Issue 4, Pages 679-690 doi: 10.1016/j.eng.2019.07.018
With the development of modern information technology—and particularly of the new generation of artificial intelligence (AI) technology—new opportunities are available for the development of the intelligent machine tool (IMT). Based on the three classical paradigms of intelligent manufacturing as defined by the Chinese Academy of Engineering, the concept, characteristics, and systemic structure of the IMT are presented in this paper. Three stages of machine tool evolution—from the manually operated machine tool (MOMT) to the IMT—are discussed, including the numerical control machine tool (NCMT), the smart machine tool (SMT), and the IMT. Furthermore, the four intelligent control principles of the IMT—namely, autonomous sensing and connection, autonomous learning and modeling, autonomous optimization and decision-making, and autonomous control and execution—are presented in detail. This paper then points out that the essential characteristic of the IMT is to acquire and accumulate knowledge through learning, and presents original key enabling technologies, including the instruction-domain-based analytical approach, theoretical and big-data-based hybrid modeling technology, and the double-code control method. Based on this research, an intelligent numerical control (INC) system and industrial prototypes of IMTs are developed. Three intelligent practices are conducted, demonstrating that the integration of the new generation of AI technology with advanced manufacturing technology is a feasible and convenient way to advance machine tools toward the IMT.
Keywords： Intelligent manufacturing Intelligent machine tool Intelligent numerical controller New-generation artificial intelligence
Heading toward Artificial Intelligence 2.0
Yunhe Pan
Engineering 2016, Volume 2, Issue 4, Pages 409-413 doi: 10.1016/J.ENG.2016.04.018
With the popularization of the Internet, permeation of sensor networks, emergence of big data, increase in size of the information community, and interlinking and fusion of data and information throughout human society, physical space, and cyberspace, the information environment related to the current development of artificial intelligence (AI) has profoundly changed. AI faces important adjustments, and scientific foundations are confronted with new breakthroughs, as AI enters a new stage: AI 2.0. This paper briefly reviews the 60-year developmental history of AI, analyzes the external environment promoting the formation of AI 2.0 along with changes in goals, and describes both the beginning of the technology and the core idea behind AI 2.0 development. Furthermore, based on combined social demands and the information environment that exists in relation to Chinese development, suggestions on the development of AI 2.0 are given.
Keywords： Artificial intelligence 2.0 Big data Crowd intelligence Cross-media Human-machine hybrid-augmented intelligence Autonomous-intelligent system
Development Strategy of Intelligent Ship Engineering Technology
Lang Shuyan, Zeng Xiaoguang, Zhang Min
Strategic Study of CAE 2019, Volume 21, Issue 6, Pages 27-32 doi: 10.15302/J-SSCAE-2019.06.005
With the rapid development of emerging technologies, intelligent ship has gradually become a hot spot for development in the shipbuilding industry. In this study, we introduced the technical classification of intelligent ships, summarized the current development status of intelligent ship technology in China and abroad, studied the characteristics of its development abroad, and analyzed the existing problems in its development in China. Furthermore, we suggest that China should pay equal attention to R & D and application of the intelligent ship technology, promote its development step by step, strengthen cooperation among the industry, university, and research institute, establish a comprehensive service mode with ship–shore integration, and further strengthen the construction of talent teams.
Keywords： ship intelligention intelligent ship technology intelligent ship
From Intelligence Science to Intelligent Manufacturing
Lihui Wang
Engineering 2019, Volume 5, Issue 4, Pages 615-618 doi: 10.1016/j.eng.2019.04.011
Research on Intelligent Manufacturing Development Strategy in China
The Research Group for Research on Intelligent Manufacturing Development Strategy
Strategic Study of CAE 2018, Volume 20, Issue 4, Pages 1-8 doi: 10.15302/J-SSCAE-2018.04.001
Intelligent manufacturing is the focus for building China into a manufacturing power. Intelligent manufacturing is a general concept under continuous development. In this paper, the intension of intelligent manufacturing is put forward. Intelligent manufacturing is categorized into three basic paradigms: digital manufacturing, smart manufacturing, and new-generation intelligent manufacturing. It is proposed that China should push forward the intelligent transformation of its manufacturing industry by adopting a technology roadmap of “parallel promotion and integrated development”. The strategic objectives, strategic guidelines, and development paths for the future development of intelligent manufacturing in China are put forward. Then some preliminary suggestions, in terms of mechanism guarantee and policies in China, including strengthening and implementing the intelligent manufacturing promotion mechanism, increasing fiscal and financial support, and deepening international exchanges and cooperation are proposed.
Keywords： new-generation intelligent manufacturing basic paradigms parallel promotion and integrated development
The key role of smart load in smart grid system
Shi Yi,Gu Weidong and Shi Jianzhong
Strategic Study of CAE 2015, Volume 17, Issue 3, Pages 10-13
This paper brings forward a new concept of “smart load” in accordance with China’s national conditions. It is the internet of things that combines the smart load with smart grid to constitute the “non-grid-connected multi-energy complementary smart grid system”. The core of the system is to transform a large number of energy-intensive industries in China into the “smart loads” that can be adapted to wind power and other renewable energy and huge fluctuations in grid output power through necessary technological innovation，thus providing Chinese government with a new path that can significantly improve the utilization efficiency of power grid and power generation equipment as well as take full advantage of high-efficient and low-cost renewable energy such as wind power pursuant to China’s national conditions.
Keywords： non-grid-connected； multi-energy collaborative； smart load； smart grid system
Intelligent Petroleum Engineering Perspective
Mohammad Ali Mirza, Mahtab Ghoroori, Zhangxin Chen
Engineering 2022, Volume 18, Issue 11, Pages 27-32 doi: 10.1016/j.eng.2022.06.009
Data-driven approaches and AI algorithms are promising enough to be relied on even more than physics-based methods; their main feed is data which is the fundamental element of each phenomenon. These algorithms learn from data and unveil unseen patterns out of it. The petroleum industry as a realm where huge volumes of data are generated every second is of great interest to this new technology. As the oil and gas industry is in the transition phase to oilfield digitization, there has been an increased drive to integrate data-driven modeling and machine learning algorithms in different petroleum engineering challenges. ML has been widely used in different areas of the industry. Many extensive studies have been devoted to exploring AI applicability in various disciplines of this industry; however, lack of two main features is noticeable. Most of the research is either not practical enough to be applicable in real-field challenges or limited to a specific problem and not generalizable. Attention must be given to data itself and the way it is classified and stored. Although there are sheer volumes of data coming from different disciplines, they reside in departmental silos and are not accessible by consumers. In order to derive as much insight as possible out of data, the data needs to be stored in a centralized repository from where the data can be readily consumed by different applications.
Keywords： Artificial intelligence Machine learning Intelligent reservoir engineering Text mining Intelligent geoscience Intelligent drilling engineering
Intelligent Drilling and Completion: A Review Review
Gensheng Li,Xianzhi Song,Shouceng Tian,Zhaopeng Zhu,
Engineering 2022, Volume 18, Issue 11, Pages 33-48 doi: 10.1016/j.eng.2022.07.014
The application of artificial intelligence (AI) has become inevitable in the petroleum industry. In drilling and completion engineering, AI is regarded as a transformative technology that can lower costs and significantly improve drilling efficiency (DE). In recent years, numerous studies have focused on intelligent algorithms and their application. Advanced technologies, such as digital twins and physics-guided neural networks, are expected to play roles in drilling and completion engineering. However, many challenges remain to be addressed, such as the automatic processing of multi-source and multi-scale data. Additionally, in intelligent drilling and completion, methods for the fusion of data-driven and physicsbased models, few-sample learning, uncertainty modeling, and the interpretability and transferability of intelligent algorithms are research frontiers. Based on intelligent application scenarios, this study comprehensively reviews the research status of intelligent drilling and completion and discusses key research areas in the future. This study aims to enhance the berthing of AI techniques in drilling and completion engineering.
Keywords： Intelligent drilling and completion Artificial intelligence Intelligent application scenarios Literature review Systematic discuss
Title Author Date Type Operation
Prospects for multi-agent collaboration and gaming: challenge, technology, and application
Yu LIU, Zhi LI, Zhizhuo JIANG, You HE
Journal Article
Multi-Peptide Adsorption on Uncharged Solid Surfaces: A Coarse-Grained Simulation Study
Ruosang Qiu, Jie Xiao, Xiao Dong Chen
Journal Article
The Application of Multi-agent Based Distributed Intelligent Control in VAV Air Conditioning System
Zhang Hongwei,Wu Aiguo,Sheng Tao
Journal Article
Intelligent Products and Equipment Led by New-Generation Artificial Intelligence
Tan Jianrong, Liu Zhenyu, Xu Jinghua
Journal Article
Intelligence Originating from Human Beings and Expanding in Industry— A View on the Development of Artificial Intelligence
Jiang Changjun, Wang Junli
Journal Article
Applications of artificial intelligence in intelligent manufacturing: a review
Bo-hu LI,Bao-cun HOU,Wen-tao YU,Xiao-bing LU,Chun-wei YANG
Journal Article
Toward Intelligent Machine Tool
Jihong Chen, Pengcheng Hu, Huicheng Zhou, Jianzhong Yang, Jiejun Xie, Yakun Jiang, Zhiqiang Gao, Chenglei Zhang
Journal Article
Development Strategy of Intelligent Ship Engineering Technology
Lang Shuyan, Zeng Xiaoguang, Zhang Min
Journal Article
Research on Intelligent Manufacturing Development Strategy in China
The Research Group for Research on Intelligent Manufacturing Development Strategy
Journal Article
Intelligent Petroleum Engineering
Mohammad Ali Mirza, Mahtab Ghoroori, Zhangxin Chen
Journal Article
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