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7th Asia Conference on Energy and Electrical Engineering (ACEEE)

作者： Wang, Feng Wang, Jiaojiao Zhou, Juntao Li, Haifeng Zheng, Quanchao Guangdong Power Grid Co Ltd Elect Power Dispatching & Control Ctr Guangzhou Peoples R China Guangdong Power Grid Co Ltd Maoming Power Supply Bur Maoming Peoples R China South China Univ Technol Sch Elect Power Engn Guangzhou Peoples R China Guangdong Yitaida Technol Dev Co Ltd Guangzhou Peoples R China

ISBN: (纸本)9798350350258;9798350350241

In recent years, large-scale construction of photovoltaic (PV) power stations has been underway, and with different construction requirements, there are more and more PV power stations of different capacity levels. The research on power stations of different levels requires frequent manual changes of system parameters, which is low in efficiency and difficult to find the optimal one. Therefore, this paper proposes an adaptive parameters optimization method for PV simulation system based on the Multi-layer Recurrent Learning and Genetic Algorithm. Firstly, the circuit parameters of the PV system are calculated based on the principle of constant input impedance. Then, the optimization task is designed based on the Multi-layer Recurrent Learning, and finally, the improved Genetic Algorithm is used to optimize the parameters of control system. The experiment results show that the method proposed in this paper can effectively realize the adaptive optimization of PV system parameters and improve the transient and steady state characteristics of the system under various complex operating conditions, providing a reference for the design of other optimization methods, with the characteristics of wide applicability, strong generality and good application prospects.

关键词： photovoltaic system parameters optimization Genetic Algorithm hierarchical learning Multi-layer Recurrent Learning

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Cutting parameters optimization by Fuzzy Synthetic Evaluation and BP Neural Network in Milling Aluminum Alloy

Cutting Parameters Optimization by Fuzzy Synthetic Evaluatio...

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10th International Conference on Machining and Advanced Manufacturing Technology

作者： Zhang, Xiaohui Guo, Guoqiang Chen, Ming Rong, Bin Han, Bing Liu, Gang Zhang, Yunshan Shanghai Jiao Tong Univ Sch Mech Engn Shanghai 200030 Peoples R China Commercial Aircraft Corp China Ltd Shanghai Aircraft Mfg Fac Shanghai Peoples R China Shanghai Tool works Co LTD Shanghai 200093 Peoples R China Changchun FAW Tool & Equipment Co Ltd Shanghai 200093 Peoples R China

ISBN: (纸本)0878492844

Aluminum alloy, as a kind of large-scaled structures, have been widely used in modern aerospace industry. In order to reduce its machining deformation, cutting parameter optimization is absolutely necessarily. By fuzzy synthetic evaluation, cutting parameters are optimized based on factors: surface roughness, residual stress, radial milling force and milling temperature. By maximal grade of membership rule, optimized values are obtained by different two methods. And by BP network with Bayesian regularization method the corresponding milling parameters are obtained too.

关键词： Milling parameters optimization Fuzzy synthetic evaluation Neural network

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Research on parameters optimization of Virtual NC milling Based on Parallelism Selection Genetic Algorithm

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International Conference on Manufacturing Science and Engineering (ICMSE 2009)

作者： Sui, Xiulin Kong, Zhengwei Ge, Jianghua Zhang, Jiatai Jin, Lijuan Harbin Engn Univ Coll Mechatron Engn Harbin 150001 Peoples R China Harbin Univ Sci & Technol Coll Mech & Power Engn Harbin 150080 Peoples R China

ISBN: (纸本)9780878492800

To resolve key technology of parameter optimization of virtual NC milling physical simulation system, a multi-objectives optimized model was set up by non-linear programming theory and resolved by improved parallelism selection genetic algorithm. It was optimized when milling characters are sufficiently considered and machine quality was guaranteed. Sub-population size is decided by weighting each optimized object and calculating adaptation to assure importance of optimized objects and fasten convergence velocity. A kind of software that can optimize milling parameters of virtual NC was developed, and optimized strategy and validity of algorithm are verified which provides technology support for realizing virtual NC milling physical system.

关键词： Virtual NC Parallelism selection genetic algorithm Milling parameters optimization

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Experimental Study and Simulation Analysis on Ball-end Cutter Milling Titanium Alloy Based on the Geometric parameters optimization

Experimental Study and Simulation Analysis on Ball-end Cutte...

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12th Conference on Machining and Advanced Manufacturing Technology

作者： Cheng, Yaonan An, Shuo Liu, Xianli Zhang, Yue Shi, Lei Harbin Univ Sci & Tech Key Lab Natl & Local United Engn High Efficiency Harbin 150080 Peoples R China

ISBN: (纸本)9783037858929

Titanium alloy materials are widely used in the field of aero-engine, the complex surface forming of key parts usually use the ball end mill. First, optimized and designed tool based on the main geometric parameters of the tool, the experimental researching on solid carbide ball end mill milling TC4 titanium alloy was performed based on orthogonal combination of geometric parameters. Second, made a concrete analysis of the milling force collected in the experiment, tool geometry parameters were optimized based on the theoretical and practical. Then analyzed the optimized tool milling force changing rules under finite element milling simulation. Influence of milling parameters on milling force was analyzed with the single factor experiment for the optimized tool, milling parameters were optimized by drawing the force curve. The above studies provide a reference for the actual production of titanium alloy semi-finishing and finishing in tool design and milling parameters selection.

关键词： Ball-end cutter parameters optimization TC4 titanium alloy Simulation analysis

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parameters optimization for decontamination and fine physical regeneration pathways of polypropylene plastics from waste lunchboxes

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JOURNAL OF HAZARDOUS MATERIALS 2024年 470卷 134247页

作者： Dong, Lipeng Zhi, Wenwu Li, Weijun Li, Jiahui GER Inst Polymer Mat Recycling Yichun 331100 Jiangxi Peoples R China Natl Engn Res Ctr WEEE Recycling Jingmen 448124 Hubeit Peoples R China Wenzhou Environm Dev & Urban Solid Waste Comprehen Wenzhou 325000 Zhejiang Peoples R China Sun Yat sen Univ Sch Mat Sci & Engn Guangzhou 510275 Guangdong Peoples R China Hunan Prov Inst Land & Resources Planning Changsha 410000 Hunan Peoples R China

Due to the development of the food delivery industry, a large amount of waste lunchboxes made of homo polypropylene (PP) plastic have been generated. This study developed a new technological strategy to effectively regenerate PP from waste lunchboxes. Through response surface curve analysis, it was found that under the optimal process conditions of hot alkali washing at 80 degree celsius, 30 min, and pH 13, the optimal contact angle was 65.55 degrees, indicating a good oil stain removal effect. By identifying and analyzing the characteristics of impurities in waste lunchboxes, a physical sorting and granulation regeneration process was constructed. And through largescale statistical analysis and data collection, it was further verified that recycled PP plastics maintained their physical stability and excellent processing performance. The quality stability of recycled PP plastics in terms of impurities content was also verified. By designing different formulations specifically, recycled PP was mixed with different virgin PP and antioxidants in appropriate proportions, and extruded into particles under 150-300 mesh filtration conditions to obtain modified recycled PP. Modified recycled PP was applied in textiles, clothing, and injection molded products. In conclusion, we achieve the up-cylcing of waste PP lunchboxes instead of downcylcing.

关键词： Waste PP lunchboxes Decontamination parameters optimization Physical recycling Upgrade regeneration

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Tremor attenuation for surgical robots using support vector machine with parameters optimization 10

Tremor attenuation for surgical robots using support vector ...

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10th International Conference on Advanced Computational Intelligence (ICACI)

作者： Luo, Jing Yang, Chenguang Dai, Shi-Lu Liu, Zhi South China Univ Technol Coll Automat Sci & Engn Guangzhou Guangdong Peoples R China Guangdong Univ Technol Sch Automat Guangzhou Guangdong Peoples R China

ISBN: (纸本)9781538643624

Reliability and accuracy of the minimally invasive surgery may be influenced by the surgeons hand tremor in the process of operation of the surgical robot. In this work, a tremor attenuation method based on machine learning is presented to track hand tremor effectively. This method is designed for filtering the interference signal with small scale sampling data and high dimension feature. First, a hybrid kernel is adopted in the proposed method to obtain a good generalization ability. Then, we introduce a optimization method to find the optimal model parameters. Besides, experimental results demonstrated effectiveness of the proposed method in the case of limited samples.

关键词： physiological tremor support vector machine particle swarm optimization parameters optimization surgical robots

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Study of parameters optimization of Organic Rankine Cycle (ORC) for Engine Waste Heat Recovery

Study of Parameters Optimization of Organic Rankine Cycle (O...

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2nd International Conference on Manufacturing Science and Engineering

作者： Zhang, Hongguang Wang, Enhua Ouyang, Minggao Fan, Boyuan Beijing Univ Technol Chaoyang Coll Environm & Energy Engn Beijing 100124 Peoples R China Tsinghua Univ State Key Lab Automot Safety & Energy Beijing 100084 Peoples R China

ISBN: (纸本)9783037850398

Energy saving and environment protection are two most important issues that today's internal combustion engine industry must tackle with. Lots of heat energy waste with the exhaust gas when the engine is running. Organic Rankine cycle (ORC) is a good method to recover the waste heat of the engine exhaust. In this paper, the mathematical model of ORC was built up in Matlab and the parameters were optimized using genetic algorithm (GA). Eight pure component organic working fluids were selected and compared. The results indicate that the evaporating pressure of the working fluid and the condensing temperature are two important parameters for ORC;the super heater also can enhance the system thermal efficiency slightly.

关键词： Internal Combustion Engine Waste Heat Recovery Organic Rankine Cycle parameters optimization Genetic Algorithm

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A New Weighted Support Vector Machine for Regression and Its parameters optimization

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4th International Conference on Intelligent Computing

作者： Mei, Liquan Zhang, Shujuan Xi An Jiao Tong Univ Sch Sci Xian 710049 Peoples R China

ISBN: (纸本)9783540859833

In this paper what we study is twofold. Firstly a new weighted support vector machine (WSVM) is introduced, in which different roles of samples are considered. It better processes the singularity in the sample than SVM. Secondly based on grid search and the solution path algorithm, a new algorithm is given to quickly find the optimum parameters. Numerical results show the effectiveness and the stability of the algorithm.

关键词： WSVM singularity regression parameters optimization

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AISGA: Multi-objective parameters optimization for countermeasures selection through genetic algorithm 21

AISGA: Multi-objective parameters optimization for counterme...

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16th International Conference on Availability, Reliability and Security (ARES)

作者： Nespoli, Pantaleone Marmol, Felix Gomez Kambourakis, Georgios Univ Murcia Dept Informat & Commun Engn Murcia Spain European Commiss Joint Res Ctr JRC I-21027 Ispra Italy

ISBN: (纸本)9781450390514

Cyberattacks targeting modern network infrastructures are increasing in number and impact. This growing phenomenon emphasizes the central role of cybersecurity and, in particular, the reaction against ongoing threats targeting assets within the protected system. Such centrality is reflected in the literature, where several works have been presented to propose full-fledged reaction methodologies to tackle offensive incidents' consequences. In this direction, the work in [18] developed an immuno-based response approach based on the application of the Artificial Immune System (AIS) methodology. That is, the AIS-powered reaction is able to calculate the optimal set of atomic countermeasure to enforce on the asset within the monitored system, minimizing the risk to which those are exposed in a more than adequate time. To further contribute to this line, the paper at hand presents AISGA, a multi-objective approach that leverages the capabilities of a Genetic Algorithm (GA) to optimize the selection of the input parameters of the AIS methodology. Specifically, AISGA selects the optimal ranges of inputs that balance the tradeoff between minimizing the global risk and the execution time of the methodology. Additionally, by flooding the AIS-powered reaction with a wide range of possible inputs, AISGA intends to demonstrate the robustness of such a model. Exhaustive experiments are executed to precisely compute the optimal ranges of parameters, demonstrating that the proposed multi-objective optimization prefers a fast-but-effective reaction.

关键词： Countermeasures selection Cyberattacks countermeasures Reaction framework parameters optimization Genetic algorithm

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An Improved Ant Colony Algorithm for PID parameters optimization

An Improved Ant Colony Algorithm for PID Parameters Optimiza...

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2nd International Conference on Intelligent Computation Technology and Automation

作者： Chen, Yibao Guo, Zhong Liu, Jiaguang Yantai Univ Sch Electromech Automobile Engn Yantai Shandong Peoples R China

ISBN: (纸本)9780769538044

In view of traditional PID controller parameters optimization by Z-N method, and none satisfactory dynamic properties can be gotten, so a new PID controller parameters optimization method based on improved Ant Colony Algorithm is put forward in this paper. Ant Colony Algorithm is a way of heuristic, which adopts parallel computation mechanism, characterized with strong robust. This paper proposes an improved algorithm based on adaptively adjusting the pheromone on routes;meanwhile, in order to avoid stagnation of the search, the range of possible pheromone trails on each solution component is limited to a maximum-minimum interval. Simulation experiment shows the proposed Ant Colony Algorithm is feasible.

关键词： Ant Colony Algorithm pheromone PID controller parameters optimization

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