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人在回路的深度强化学习算法及其在自动驾驶智能决策中的应用 Article

吴京达, 黄志宇, 胡中旭, 吕辰

《工程（英文）》 2023年第21卷第2期页码 75-91 doi: 10.1016/j.eng.2022.05.017

摘要：因为人类在复杂场景中表现出稳健性和适应性，所以将人类引入人工智能（AI）的训练回路并利用人类智能进一步提升机器学习算法变得至关重要。基于这种人在回路的指导机制，本研究开发一种基于修正策略和价值网络的改良的演员-评论家架构（actor-critic architecture）。所提出的Hug-DRL的快速收敛允许实时的人类指导行为融合到智能体的训练回路中，进一步提高了DRL的效率和性能。本研究通过40 名受试者的人在回路实验对开发的方法进行了验证，并与其他最先进的学习方法进行了比较。

关键词：人在回路AI 深度强化学习人类指导自动驾驶

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工业机器人在智能制造中的角色

戴家鹏

《工程（英文）》 2018年第4卷第4期页码 440-445 doi: 10.1016/j.eng.2018.07.012

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Platform governance in the era of AI and the digital economy

《工程管理前沿（英文）》 2023年第10卷第1期页码 177-182 doi: 10.1007/s42524-022-0241-1

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秦山核电厂二回路系统水化学的改进

陶钧,孔德萍

《中国工程科学》 2008年第10卷第1期页码 91-96

摘要：

核电厂二回路系统的水质控制与关键重要设备蒸汽发生器的运行寿命有着密切的关系，秦山核电厂运行16年来，随着秦山核电厂二回路系统水化学管理的不断改进，二回路系统的水质不断改善。这些管理改进主要体现在管理理念的改变，二回路系统高AVT（全会法处理方式）处理、对凝结水精处理装置的优化运行以及大修及启动过程的严格控制等。二回路水化学的改善确保了蒸汽发生器传热管的结构完整性。

关键词：二回路水化学 WANO化学性能指标

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Bridging the gap: Neuro-Symbolic Computing for advanced AI applications in construction

《工程管理前沿（英文）》页码 727-735 doi: 10.1007/s42524-023-0266-0

摘要： Deep Learning (DL) has revolutionized the field of Artificial Intelligence (AI) in various domains such as computer vision (CV) and natural language processing. However, DL models have limitations including the need for large labeled datasets, lack of interpretability and explainability, potential bias and fairness issues, and limitations in common sense reasoning and contextual understanding. On the other side, DL has shown significant potential in construction for safety and quality inspection tasks using CV models. However, current CV approaches may lack spatial context and measurement capabilities, and struggle with complex safety and quality requirements. The integration of Neuro-Symbolic Computing (NSC), an emerging field that combines DL and symbolic reasoning, has been proposed as a potential solution to address these limitations. NSC has the potential to enable more robust, interpretable, and accurate AI systems in construction by harnessing the strengths of DL and symbolic reasoning. The combination of symbolism and connectionism in NSC can lead to more efficient data usage, improved generalization ability, and enhanced interpretability. Further research and experimentation are needed to effectively integrate NSC with large models and advance CV technologies for precise reporting of safety and quality inspection results in construction.

关键词： advanced AI in construction safety and quality inspection Neuro-Symbolic Computing Deep Learning computer vision

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我国企业人工智能应用现状与挑战

徐文伟,肖立志,刘合

《中国工程科学》 2022年第24卷第6期页码 173-183 doi: 10.15302/J-SSCAE-2022.07.010

摘要：在国家宏观层面，有必要构建更友好的AI产业生态环境，促进AI全产业链协同发展；以更有力的具体举措支持AI产业的技术研发，特别是全栈AI、AI基础平台及工具体系、AI根技术等，提高我国AI核心技术的自主可控能力；鼓励企业积极实施数字化转型，采用AI技术进行智能化升级，形成AI产业技术研发、企业AI落地创新的强耦合及双向循环。">6]，旨在构建值得全球信赖的AI中心，加强欧盟范围内AI的使用、投资和创新活动。

在我国，AI技术持续创新和突破，AI资源持续优化整合，AI产业结构逐渐完善。鉴于工业生产工况的复杂多变，数据驱动的AI模型可能遇到从未“见过”的工况，需要以“边云”协同的系统能力建立反馈回路，从而对AI应用的异常结果进行监控和迭代

建议支持AI产业链发展，扶持全栈AI国产化，完善AI基础平台及工具体系，培育国产AI根技术，提高AI核心技术的自主可控能力。

关键词：人工智能企业场景智能解决方案落地应用全栈AI AI根技术

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卫星主动控温回路的设计模型与算法

李运泽,杨娟,宁献文,王晓明,石晓波

《中国工程科学》 2008年第10卷第7期页码 48-50

摘要：

使用电加热器的卫星主动控温回路是一种重要的主动热控措施，通过简明扼要的机理分析建立起该主动控温过程中受控对象温度变化的动态方程，得出了稳态控温、瞬态控温两种基本的控温模式下主动控温回路电加热器功率需求的计算表达式，给出了进行主动控温回路电加热器热功率设计计算的一般流程，较详细地分析了一个具体设计算例，为卫星主动控温回路设计计算提供了简便的计算模型和方法

关键词：卫星主动热控制主动控温回路模型与算法

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Intelligent high-speed cutting database system development

XIANG Kejun, LIU Zhanqiang, AI Xing

《机械工程前沿（英文）》 2008年第3卷第2期页码 180-188 doi: 10.1007/s11465-008-0038-x

摘要： In this paper, the components of a high-speed cutting system are analyzed firstly. The component variables of the high-speed cutting system are classified into four types: uncontrolled variables, process variables, control variables, and output variables. The relationships and interactions of these variables are discussed. Then, by analyzing and comparing intelligent reasoning methods frequently used, the hybrid reasoning is employed to build the high-speed cutting database system. Then, the data structures of high-speed cutting case base and databases are determined. Finally, the component parts and working process of the high-speed cutting database system on the basis of hybrid reasoning are presented.

关键词： control hybrid reasoning process component uncontrolled

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Application of AI techniques in monitoring and operation of power systems

David Wenzhong GAO, Qiang WANG, Fang ZHANG, Xiaojing YANG, Zhigang HUANG, Shiqian MA, Qiao LI, Xiaoyan GONG, Fei-Yue WANG

《能源前沿（英文）》 2019年第13卷第1期页码 71-85 doi: 10.1007/s11708-018-0589-4

摘要： In recent years, the artificial intelligence (AI) technology is becoming more and more popular in many areas due to its amazing performance. However, the application of AI techniques in power systems is still in its infancy. Therefore, in this paper, the application potentials of AI technologies in power systems will be discussed by mainly focusing on the power system operation and monitoring. For the power system operation, the problems, the demands, and the possible applications of AI techniques in control, optimization, and decision making problems are discussed. Subsequently, the fault detection and stability analysis problems in power system monitoring are studied. At the end of the paper, a case study to use the neural network (NN) for power flow analysis is provided as a simple example to demonstrate the viability of AI techniques in solving power system problems.

关键词： power system operation and monitoring artificial intelligence (AI) deep learning power flow analysis

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Ni-Co bimetallic catalyst for CH

Xiaohong LI, Jun AI, Wenying LI, Dongxiong LI

《化学科学与工程前沿（英文）》 2010年第4卷第4期页码 476-480 doi: 10.1007/s11705-010-0512-y

摘要： A co-precipitation method was employed to prepare Ni/Al O -ZrO , Co/Al O -ZrO and Ni-Co/Al O -ZrO catalysts. Their properties were characterized by N adsorption (BET), thermogravimetric analysis TGA , temperature-programmed reduction (TPR), temperature-programmed desorption (CO -TPD), and temperature-programmed surface reaction (CH -TPSR and CO -TPSR). Ni-Co/Al O -ZrO bimetallic catalyst has good performance in the reduction of active components Ni, Co and CO adsorption. Compared with mono-metallic catalyst, bimetallic catalyst could provide more active sites and CO adsorption sites (C+ CO = 2CO) for the methane-reforming reaction, and a more appropriate force formed between active components and composite support (SMSI) for the catalytic reaction. According to the CH -CO -TPSR, there were 80.9% and 81.5% higher CH and CO conversion over Ni-Co/Al O -ZrO catalyst, and its better resistance to carbon deposition, less than 0.5% of coke after 4 h reaction, was found by TGA. The high activity and excellent anti-coking of the Ni-Co/Al O -ZrO catalyst were closely related to the synergy between Ni and Co active metal, the strong metal-support interaction and the use of composite support.

关键词： Ni-Co bimetallic catalyst composite support CH₄ reforming with CO₂

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中国人工智能的伦理原则及其治理技术发展 Review

吴文峻,黄铁军,龚克

《工程（英文）》 2020年第6卷第3期页码 302-309 doi: 10.1016/j.eng.2019.12.015

摘要：

伦理原则和治理技术对于人工智能（AI）的健康和可持续发展至关重要。为了实现AI造福人类社会这一长期目标，中国政府、研究机构和企业已经发布了AI的伦理原则，并启动了研究AI治理技术的项目。此外，本文总结了AI治理研究中所面临的主要挑战，并讨论了未来的研究方向。

关键词：人工智能伦理，人工智能治理技术，机器学习，隐私，安全，公平

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自主遥控水下机器人在马里亚纳海沟挑战者深渊基于地形匹配定位 Research

王健1,2,唐元贵1,2,陈传绪3,李吉旭1,2,陈聪1,2,张艾群1,2,3,李一平1,2,李硕1,2

《信息与电子工程前沿（英文）》 2020年第21卷第5期页码 649-808 doi: 10.1631/FITEE.1900556

摘要：截至目前，地球海洋最大深度记录约为11 000米，位于西太平洋马里亚纳海沟。海斗号自主遥控水下机器人主要用于地球海洋最深处科学考察。对全海深潜水器而言，声学定位技术最有效且被广为利用。11 000米级声学定位系统相对庞大且复杂，同时需要装备兼容声学设备的专用科考船。作为一个紧凑的测试平台，海斗号无法装备大体积大重量的LBL/USBL。潜水器在下潜至11 000米海试过程中，由于受流体动力学及洋流不确定性影响，其水平漂移难以避免。海斗号记录的最大深度为10 905米，而确定该最深点位置具有一定挑战。基于多波束声呐形成的测深图，可采用地形轮廓匹配（TERCOM）方法进行地形匹配定位。TERCOM方法可稳定推测准确位置，因其对初始位置误差不敏感。最终匹配结果揭示了在参考地形图中的最佳估计位置。

关键词：自主遥控水下机器人；全海深；挑战者深渊；马里亚纳海沟；地形轮廓匹配

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One-step synthesis of

Kuiyi YOU, Fangfang ZHAO, Xueyan LONG, Pingle LIU, Qiuhong AI, Hean LUO

《化学科学与工程前沿（英文）》 2012年第6卷第4期页码 389-394 doi: 10.1007/s11705-012-1218-0

摘要： A simple and efficient approach for the synthesis of -caprolactam via the liquid phase nitrosation of cyclohexane and nitrosyl sulfuric acid in the presence of concentrated sulfuric acid has been developed. A series of novel AlVPO composites were prepared by an impregnation method and the composites were then employed to catalyze the nitrosation reaction of cyclohexane and nitrosyl sulfuric acid. Compared to the reaction using fuming sulfuric acid, the selectivity for the desired product was significantly improved using this one-step catalytic process. This method affords a shortcut to prepare -caprolactam and its analogs from cyclohexane.

关键词： cyclohexane ?-caprolactam AlVPO composite catalysts one-step synthesis concentrated sulfuric acid

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Ensemble unit and AI techniques for prediction of rock strain

Pradeep T; Pijush SAMUI; Navid KARDANI; Panagiotis G ASTERIS

《结构与土木工程前沿（英文）》 2022年第16卷第7期页码 858-870 doi: 10.1007/s11709-022-0831-3

摘要： The behavior of rock masses is influenced by a variety of forces, with measurement of stress and strain playing the most critical roles in assessing deformation. The laboratory test for determining strain at each location within rock samples is expensive and difficult but rock strain data are important for predicting failure of rock material. Many researchers employ AI technology in order to solve these difficulties. AI algorithms such as gradient boosting machine (GBM), support vector regression (SVR), random forest (RF), and group method of data handling (GMDH) are used to efficiently estimate the strain at every point within a rock sample. Additionally, the ensemble unit (EnU) may be utilized to evaluate rock strain. In this study, 3000 experimental data are used for the purpose of prediction. The obtained strain values are then evaluated using various statistical parameters and compared to each other using EnU. Ranking analysis, stress-strain curve, Young’s modulus, Poisson’s ratio, actual vs. predicted curve, error matrix and the Akaike’s information criterion (AIC) values are used for comparing models. The GBM model achieved 98.16% and 99.98% prediction accuracy (in terms of values of R²) in the longitudinal and lateral dimensions, respectively, during the testing phase. The GBM model, based on the experimental data, has the potential to be a new option for engineers to use when assessing rock strain.

关键词： prediction strain ensemble unit rank analysis error matrix

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Novel quantum-inspired firefly algorithm for optimal power quality monitor placement

Ling Ai WONG,Hussain SHAREEF,Azah MOHAMED,Ahmad Asrul IBRAHIM

《能源前沿（英文）》 2014年第8卷第2期页码 254-260 doi: 10.1007/s11708-014-0302-1

摘要： The application of a quantum-inspired firefly algorithm was introduced to obtain optimal power quality monitor placement in a power system. The conventional binary firefly algorithm was modified by using quantum principles to attain a faster convergence rate that can improve system performance and to avoid premature convergence. In the optimization process, a multi-objective function was used with the system observability constraint, which is determined via the topological monitor reach area concept. The multi-objective function comprises three functions: number of required monitors, monitor overlapping index, and sag severity index. The effectiveness of the proposed method was verified by applying the algorithm to an IEEE 118-bus transmission system and by comparing the algorithm with others of its kind.

关键词： quantum-inspired binary firefly algorithm topological monitor reach area power quality