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QPSO-ILF-ANN-based optimization of TBM control parameters considering tunneling energy efficiency

《结构与土木工程前沿（英文）》 2023年 第17卷 第1期   页码 25-36 doi: 10.1007/s11709-022-0908-z

摘要： In recent years, tunnel boring machines (TBMs) have been widely used in tunnel construction. However, the TBM control parameters set based on operator experience may not necessarily be suitable for certain geological conditions. Hence, a method to optimize TBM control parameters using an improved loss function-based artificial neural network (ILF-ANN) combined with quantum particle swarm optimization (QPSO) is proposed herein. The purpose of this method is to improve the TBM performance by optimizing the penetration and cutterhead rotation speeds. Inspired by the regularization technique, a custom artificial neural network (ANN) loss function based on the penetration rate and rock-breaking specific energy as TBM performance indicators is developed in the form of a penalty function to adjust the output of the network. In addition, to overcome the disadvantage of classical error backpropagation ANNs, i.e., the ease of falling into a local optimum, QPSO is adopted to train the ANN hyperparameters (weight and bias). Rock mass classes and tunneling parameters obtained in real time are used as the input of the QPSO-ILF-ANN, whereas the cutterhead rotation speed and penetration are specified as the output. The proposed method is validated using construction data from the Songhua River water conveyance tunnel project. Results show that, compared with the TBM operator and QPSO-ANN, the QPSO-ILF-ANN effectively increases the TBM penetration rate by 14.85% and 13.71%, respectively, and reduces the rock-breaking specific energy by 9.41% and 9.18%, respectively.

关键词： tunnel boring machine     control parameter optimization     quantum particle swarm optimization     artificial neural network     tunneling energy efficiency    

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Ant colony optimization for assembly sequence planning based on parameters optimization

Zunpu HAN, Yong WANG, De TIAN

《机械工程前沿（英文）》 2021年 第16卷 第2期   页码 393-409 doi: 10.1007/s11465-020-0613-3

摘要： As an important part of product design and manufacturing, assembly sequence planning (ASP) has a considerable impact on product quality and manufacturing costs. ASP is a typical NP-complete problem that requires effective methods to find the optimal or near-optimal assembly sequence. First, multiple assembly constraints and rules are incorporated into an assembly model. The assembly constraints and rules guarantee to obtain a reasonable assembly sequence. Second, an algorithm called SOS-ACO that combines symbiotic organisms search (SOS) and ant colony optimization (ACO) is proposed to calculate the optimal or near-optimal assembly sequence. Several of the ACO parameter values are given, and the remaining ones are adaptively optimized by SOS. Thus, the complexity of ACO parameter assignment is greatly reduced. Compared with the ACO algorithm, the hybrid SOS-ACO algorithm finds optimal or near-optimal assembly sequences in fewer iterations. SOS-ACO is also robust in identifying the best assembly sequence in nearly every experiment. Lastly, the performance of SOS-ACO when the given ACO parameters are changed is analyzed through experiments. Experimental results reveal that SOS-ACO has good adaptive capability to various values of given parameters and can achieve competitive solutions.

关键词： assembly sequence planning     ant colony optimization     symbiotic organisms search     parameter optimization    

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Multi-objective optimization of cutting parameters in high-speed milling based on grey relational analysis

Tao FU, Jibin ZHAO, Weijun LIU

《机械工程前沿（英文）》 2012年 第7卷 第4期   页码 445-452 doi: 10.1007/s11465-012-0338-z

摘要：

This paper investigates optimization problem of the cutting parameters in high-speed milling on NAK80 mold steel. An experiment based on the technology of Taguchi is performed. The objective is to establish a correlation among spindle speed, feed per tooth and depth of cut to the three directions of cutting force in the milling process. In this study, the optimum cutting parameters are obtained by the grey relational analysis. Moreover, the principal component analysis is applied to evaluate the weights so that their relative significance can be described properly and objectively. The results of experiments show that grey relational analysis coupled with principal component analysis can effectively acquire the optimal combination of cutting parameters and the proposed approach can be a useful tool to reduce the cutting force.

关键词： high-speed milling     grey relational analysis     principal component analysis     parameters optimization    

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Control efficiency optimization and Sobol’s sensitivity indices of MTMDs design parameters for buffeting

Nazim Abdul NARIMAN

《结构与土木工程前沿（英文）》 2017年 第11卷 第1期   页码 66-89 doi: 10.1007/s11709-016-0356-8

摘要： This paper studies optimization of three design parameters (mass ratio, frequency ratio and damping ratio) of multiple tuned mass dampers MTMDs that are applied in a cable stayed bridge excited by a strong wind using minimax optimization technique. ABAQUS finite element program is utilized to run numerical simulations with the support of MATLAB codes and Fast Fourier Transform FFT technique. The optimum values of these three parameters are validated with two benchmarks from the literature, first with Wang and coauthors and then with Lin and coauthors. The validation procedure detected a good agreement between the results. Box-Behnken experimental method is dedicated to formulate the surrogate models to represent the control efficiency of the vertical and torsional vibrations. Sobol’s sensitivity indices are calculated for the design parameters in addition to their interaction orders. The optimization results revealed better performance of the MTMDs in controlling the vertical and the torsional vibrations for higher mode shapes. Furthermore, the calculated rational effects of each design parameter facilitate to increase the control efficiency of the MTMDs in conjunction with the support of the surrogate models.

关键词： MTMDs     power spectral density     fast Fourier transform     minimax optimization technique     Sobol’s sensitivity indices     Box-Behnken method    

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Multidisciplinary co-design optimization of structural and control parameters for bucket wheel reclaimer

Yongliang YUAN, Liye LV, Shuo WANG, Xueguan SONG

《机械工程前沿（英文）》 2020年 第15卷 第3期   页码 406-416 doi: 10.1007/s11465-019-0578-2

摘要： Bucket wheel reclaimer (BWR) is an extremely complex engineering machine that involves multiple disciplines, such as structure, dynamics, and electromechanics. The conventional design strategy, namely, sequential strategy, is structural design followed by control optimization. However, the global optimal solution is difficult to achieve because of the discoordination of structural and control parameters. The co-design strategy is explored to address the aforementioned problem by combining the structural and control system design based on simultaneous dynamic optimization approach. The radial basis function model is applied for the planning of the rotation speed considering the relationships of subsystems to minimize the energy consumption per volume. Co-design strategy is implemented to resolve the optimization problem, and numerical results are compared with those of sequential strategy. The dynamic response of the BWR is also analyzed with different optimization strategies to evaluate the advantages of the strategies. Results indicate that co-design strategy not only can reduce the energy consumption of the BWR but also can achieve a smaller vibration amplitude than the sequential strategy.

关键词： bucket wheel reclaimer     co-design     energy-minimum optimization     sequential strategy    

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Dymola-based multi-parameters integrated optimization for high speed transfer system of LED chip sorter

Jie OUYANG, Bin LI, Shihua GONG

《机械工程前沿（英文）》 2013年 第8卷 第2期   页码 118-126 doi: 10.1007/s11465-013-0253-y

摘要：

To enhance the performance of high speed transfer system of LED chip sorting equipment, its control parameters need to be well matching with the mechanical system. In practical issues, it is difficult and time-consuming work to get these parameters matched because their selection is strongly depended on individuals. In current work, an integrated optimization method was carried out to solve this problem, in which the multiple control parameters optimization, modeling and simulation were included, i.e., a multi-domain model of transfer system performed on Dymola platform. Based on this model, the searching area of the key control parameters was narrowed by performing integrated optimization. After that a group of parameters were selected from this narrowed area to perform the equipment’s controls. The result showed this method possesses a simple and reliable nature. The optimal solutions also indicated that the optimized control parameters can well satisfy the requirements of transfer system. On the other hand, it greatly reduced the engineering adjustment time by using this method.

关键词： LED chip sorter     multi-domain modeling and simulation     parameter optimization     modelica language    

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Optimization of process parameters for mature landfill leachate pretreatment using MAP precipitation

Wei LI, Xiaowen DING, Min LIU, Yuewen GUO, Lei LIU

《环境科学与工程前沿（英文）》 2012年 第6卷 第6期   页码 892-900 doi: 10.1007/s11783-012-0440-9

摘要： Chemical precipitation is a useful technology as a pretreatment to treat mature landfill leachate with high concentrations of ammonium-nitrogen ( ) and refractory organic compounds. Orthogonal experiments and factorial experiments were carried out to determine the optimal conditions enhancing the magnesium ammonium phosphate (MAP) precipitation process, and the experimental results demonstrated that the removal rate of was more than 85% when MgO and NaH PO ·2H O were applied as external sources of magnesium and phosphorous under the optimal conditions that molar ratio n(Mg)∶n(N)∶n(P) = 1.4∶1∶0.8, reaction time 60 min, original pH of leachate and settling time 30 min. In the precipitation process, pH could be maintained at the optimal range of 8–9.5 because MgO could release hydroxide ions to consume hydrogen ions. Calcium ions and carbonate ions existed in the leachate could affect the precipitation process, which resulted in the decrease of removal efficiency. The residues of MAP sediments decomposed by heating under alkaline conditions can be reused as the sources of phosphorous and magnesium for the removal of high concentrations of , and up to 90% of ammonium could be released under molar ratio of n[OH]∶n[MAP] = 2.5∶1, heating temperature 90°C and heating time 2h.

关键词： magnesium ammonium phosphate precipitation     mature landfill leachate     optimization     ammonium-nitrogen    

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Optimization of process parameters for preparation of powdered activated coke to achieve maximum SO

Binxuan ZHOU, Tao WANG, Tianming XU, Cheng LI, Yuan ZHAO, Jiapeng FU, Zhen ZHANG, Zhanlong SONG, Chunyuan MA

《能源前沿（英文）》 2021年 第15卷 第1期   页码 159-169 doi: 10.1007/s11708-020-0719-7

摘要： Powdered activated coke (PAC) is a good adsorbent of SO , but its adsorption capacity is affected by many factors in the preparation process. To prepare the PAC with a high SO adsorption capacity using JJ-coal under flue gas atmosphere, six parameters (oxygen-coal equivalent ratio, reaction temperature, reaction time, O concentration, CO concentration, and H O concentration) were screened and optimized using the response surface methodology (RSM). The results of factor screening experiment show that reaction temperature, O concentration, and H O (g) concentration are the significant factors. Then, a quadratic polynomial regression model between the significant factors and SO adsorption capacity was established using the central composite design (CCD). The model optimization results indicate that when reaction temperature is 904.74°C, O concentration is 4.67%, H O concentration is 27.98%, the PAC (PAC-OP) prepared had a higher SO adsorption capacity of 68.15 mg/g while its SO adsorption capacity from a validation experiment is 68.82 mg/g, and the error with the optimal value is 0.98%. Compared to two typical commercial activated cokes (ACs), PAC-OP has relatively more developed pore structures, and its and are 349 m /g and 0.1475 cm /g, significantly higher than the 186 m /g and 0.1041 cm /g of AC1, and the 132 m /g and 0.0768 cm /g of AC2. Besides, it also has abundant oxygen-containing functional groups, its surface O content being 12.09%, higher than the 10.42% of AC1 and 10.49% of AC2. Inevitably, the SO adsorption capacity of PAC-OP is also significantly higher than that of both AC1 and AC2, which is 68.82 mg/g versus 32.53 mg/g and 24.79 mg/g, respectively.

关键词： powdered activated coke (PAC)     SO2 adsorption capacity     parameters optimization     response surface methodology    

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一种大偏心皮卫星分离参数复合优化方法 None

Lai TENG, Zhong-he JIN

《信息与电子工程前沿（英文）》 2018年 第19卷 第5期   页码 685-698 doi: 10.1631/FITEE.1700416

摘要： 航天飞行器的分离参数直接影响它的飞行轨迹，如果分离参数超过它能承受的极限，则飞行器难以调整飞行姿态，可能造成飞行器偏离轨道或坠毁。提出一种将角速度与外矩结合的大偏心皮卫星分离参数复合优化方法。通过改变弹性发射装置位置，在分离机构变化较小情况下，有效控制飞行器弹出过程。给出了角速度偏差的原因和不可信的优化结果，并对不可信的优化结果进行分析。通过地面无重力试验对该优化方法进行验证。仿真和试验结果表明，该优化方法能有效优化大偏心皮卫星的分离参数。该方法特别适用于固定和非稳定状态弹性参数、各种弹性装置的分布以及难以校正姿态的大偏心航天飞行器，在实际应用中具有通用性和易操作性。

关键词： 皮卫星；星箭分离机构；分离参数；参数优化    

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Robust design of configurations and parameters of adaptable products

Jian ZHANG,Yongliang CHEN,Deyi XUE,Peihua GU

《机械工程前沿（英文）》 2014年 第9卷 第1期   页码 1-14 doi: 10.1007/s11465-014-0296-8

摘要：

An adaptable product can satisfy different customer requirements by changing its configuration and parameter values during the operation stage. Design of adaptable products aims at reducing the environment impact through replacement of multiple different products with single adaptable ones. Due to the complex architecture, multiple functional requirements, and changes of product configurations and parameter values in operation, impact of uncertainties to the functional performance measures needs to be considered in design of adaptable products. In this paper, a robust design approach is introduced to identify the optimal design configuration and parameters of an adaptable product whose functional performance measures are the least sensitive to uncertainties. An adaptable product in this paper is modeled by both configurations and parameters. At the configuration level, methods to model different product configuration candidates in design and different product configuration states in operation to satisfy design requirements are introduced. At the parameter level, four types of product/operating parameters and relations among these parameters are discussed. A two-level optimization approach is developed to identify the optimal design configuration and its parameter values of the adaptable product. A case study is implemented to illustrate the effectiveness of the newly developed robust adaptable design method.

关键词： adaptable product     robust design     optimization     uncertainties    

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Multi-objective optimization of process parameters in Electro-Discharge Diamond Face Grinding based on

Ravindra Nath YADAV, Vinod YADAVA, G.K. SINGH

《机械工程前沿（英文）》 2013年 第8卷 第3期   页码 319-332 doi: 10.1007/s11465-013-0269-3

摘要：

The effective study of hybrid machining processes (HMPs), in terms of modeling and optimization has always been a challenge to the researchers. The combined approach of Artificial Neural Network (ANN) and Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) has attracted attention of researchers for modeling and optimization of the complex machining processes. In this paper, a hybrid machining process of Electrical Discharge Face Grinding (EDFG) and Diamond Face Grinding (DFG) named as Electrical Discharge Diamond face Grinding (EDDFG) have been studied using a hybrid methodology of ANN-NSGA-II. In this study, ANN has been used for modeling while NSGA-II is used to optimize the control parameters of the EDDFG process. For observations of input-output relations, the experiments were conducted on a self developed face grinding setup, which is attached with the ram of EDM machine. During experimentation, the wheel speed, pulse current, pulse on-time and duty factor are taken as input parameters while output parameters are material removal rate (MRR) and average surface roughness (Ra). The results have shown that the developed ANN model is capable to predict the output responses within the acceptable limit for a given set of input parameters. It has also been found that hybrid approach of ANN-NSGA-II gives a set of optimal solutions for getting appropriate value of outputs with multiple objectives.

关键词： hybrid machining processes (HMPs)     electrical discharge diamond grinding (EDDG)     artificial neural network (ANN)     genetic algorithm     modeling and optimization    

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Multi-objective optimization of combustion, performance and emission parameters in a jatropha biodiesel

Sunil Dhingra,Gian Bhushan,Kashyap Kumar Dubey

《机械工程前沿（英文）》 2014年 第9卷 第1期   页码 81-94 doi: 10.1007/s11465-014-0287-9

摘要：

The present work studies and identifies the different variables that affect the output parameters involved in a single cylinder direct injection compression ignition (CI) engine using jatropha biodiesel. Response surface methodology based on Central composite design (CCD) is used to design the experiments. Mathematical models are developed for combustion parameters (Brake specific fuel consumption (BSFC) and peak cylinder pressure (Pmax)), performance parameter brake thermal efficiency (BTE) and emission parameters (CO, NOx, unburnt HC and smoke) using regression techniques. These regression equations are further utilized for simultaneous optimization of combustion (BSFC, Pmax), performance (BTE) and emission (CO, NOx, HC, smoke) parameters. As the objective is to maximize BTE and minimize BSFC, Pmax, CO, NOx, HC, smoke, a multi-objective optimization problem is formulated. Non-dominated sorting genetic algorithm-II is used in predicting the Pareto optimal sets of solution. Experiments are performed at suitable optimal solutions for predicting the combustion, performance and emission parameters to check the adequacy of the proposed model. The Pareto optimal sets of solution can be used as guidelines for the end users to select optimal combination of engine output and emission parameters depending upon their own requirements.

关键词： jatropha biodiesel     fuel properties     response surface methodology     multi-objective optimization     non-dominated sorting genetic algorithm-II    

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Wastewater-nitrogen removal using polylactic acid/starch as carbon source: Optimization of operatingparameters using response surface methodology

Yan GUO, Chuanfu WU, Qunhui WANG, Min YANG, Qiqi HUANG, Markus MAGEP, Tianlong ZHENG

《环境科学与工程前沿（英文）》 2016年 第10卷 第4期 doi: 10.1007/s11783-016-0845-y

摘要： The use of PLA/starch blends for nitrogen removal was achieved. The influence of different operating parameters on responses was verified using RSM. The conditions for desired responses were successfully optimized simultaneously. Blends material may have a promising application prospect in the future. Nitrogen removal from ammonium-containing wastewater was conducted using polylactic acid (PLA)/starch blends as carbon source and carrier for functional bacteria. The exclusive and interactive influences of operating parameters (i.e., temperature, pH, stirring rate, and PLA-to-starch ratio (PLA proportion)) on nitrification ( ), denitrification ( ), and COD release rates ( ) were investigated through response surface methodology. Experimental results indicated that nitrogen removal could be successfully achieved in the PLA/starch blends through simultaneous nitrification and denitrification. The carbon release rate of the blends was controllable. The sensitivity of , , and to different operating parameters also differed. The sequence for each response was as follows: for , pH>stirring rate>PLA proportion>temperature; for , pH>PLA proportion>temperature>stirring rate; and for , stirring rate>pH>PLA proportion>temperature. In this study, the following optimum conditions were observed: temperature, 32.0°C; pH 7.7; stirring rate, 200.0 r·min ; and PLA proportion, 0.4. Under these conditions, , , and were 134.0 μg-N·g-blend ·h , 160.9 μg-N·g-blend ·h , and 7.6 × 10 μg-O·g-blend ·h , respectively. These results suggested that the PLA/starch blends may be an ideal packing material for nitrogen removal.

关键词： Nitrogen removal     Polylactic acid     Starch     Carbon source     Response surface methodology    

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Optimization of thread partitioning parameters in speculative multithreading based on artificial immune

Yu-xiang LI,Yin-liang ZHAO,Bin LIU,Shuo JI

《信息与电子工程前沿（英文）》 2015年 第16卷 第3期   页码 205-216 doi: 10.1631/FITEE.1400172

摘要： Thread partition plays an important role in speculative multithreading (SpMT) for automatic parallelization of irregular programs. Using unified values of partition parameters to partition different applications leads to the fact that every application cannot own its optimal partition scheme. In this paper, five parameters affecting thread partition are extracted from heuristic rules. They are the dependence threshold (DT), lower limit of thread size (TSL), upper limit of thread size (TSU), lower limit of spawning distance (SDL), and upper limit of spawning distance (SDU). Their ranges are determined in accordance with heuristic rules, and their step-sizes are set empirically. Under the condition of setting speedup as an objective function, all combinations of five threshold values form the solution space, and our aim is to search for the best combination to obtain the best thread granularity, thread dependence, and spawning distance, so that every application has its best partition scheme. The issue can be attributed to a single objective optimization problem. We use the artificial immune algorithm (AIA) to search for the optimal solution. On Prophet, which is a generic SpMT processor to evaluate the performance of multithreaded programs, Olden benchmarks are used to implement the process. Experiments show that we can obtain the optimal parameter values for every benchmark, and Olden benchmarks partitioned with the optimized parameter values deliver a performance improvement of 3.00% on a 4-core platform compared with a machine learning based approach, and 8.92% compared with a heuristics-based approach.

关键词： Speculative multithreading     Thread partitioning     Artificial immune algorithm    

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Intelligent methods for the process parameter determination of plastic injection molding

Huang GAO, Yun ZHANG, Xundao ZHOU, Dequn LI

《机械工程前沿（英文）》 2018年 第13卷 第1期   页码 85-95 doi: 10.1007/s11465-018-0491-0

摘要：

Injection molding is one of the most widely used material processing methods in producing plastic products with complex geometries and high precision. The determination of process parameters is important in obtaining qualified products and maintaining product quality. This article reviews the recent studies and developments of the intelligent methods applied in the process parameter determination of injection molding. These intelligent methods are classified into three categories: Case-based reasoning methods, expert system-based methods, and data fitting and optimization methods. A framework of process parameter determination is proposed after comprehensive discussions. Finally, the conclusions and future research topics are discussed.

关键词： injection molding     intelligent methods     process parameters     optimization    

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标题 作者 时间 类型 操作

QPSO-ILF-ANN-based optimization of TBM control parameters considering tunneling energy efficiency

期刊论文

Ant colony optimization for assembly sequence planning based on parameters optimization

Zunpu HAN, Yong WANG, De TIAN

期刊论文

Multi-objective optimization of cutting parameters in high-speed milling based on grey relational analysis

Tao FU, Jibin ZHAO, Weijun LIU

期刊论文

Control efficiency optimization and Sobol’s sensitivity indices of MTMDs design parameters for buffeting

Nazim Abdul NARIMAN

期刊论文

Multidisciplinary co-design optimization of structural and control parameters for bucket wheel reclaimer

Yongliang YUAN, Liye LV, Shuo WANG, Xueguan SONG

期刊论文

Dymola-based multi-parameters integrated optimization for high speed transfer system of LED chip sorter

Jie OUYANG, Bin LI, Shihua GONG

期刊论文

Optimization of process parameters for mature landfill leachate pretreatment using MAP precipitation

Wei LI, Xiaowen DING, Min LIU, Yuewen GUO, Lei LIU

期刊论文

Optimization of process parameters for preparation of powdered activated coke to achieve maximum SO

Binxuan ZHOU, Tao WANG, Tianming XU, Cheng LI, Yuan ZHAO, Jiapeng FU, Zhen ZHANG, Zhanlong SONG, Chunyuan MA

期刊论文

一种大偏心皮卫星分离参数复合优化方法

Lai TENG, Zhong-he JIN

期刊论文

Robust design of configurations and parameters of adaptable products

Jian ZHANG,Yongliang CHEN,Deyi XUE,Peihua GU

期刊论文

Multi-objective optimization of process parameters in Electro-Discharge Diamond Face Grinding based on

Ravindra Nath YADAV, Vinod YADAVA, G.K. SINGH

期刊论文

Multi-objective optimization of combustion, performance and emission parameters in a jatropha biodiesel

Sunil Dhingra,Gian Bhushan,Kashyap Kumar Dubey

期刊论文

Wastewater-nitrogen removal using polylactic acid/starch as carbon source: Optimization of operatingparameters using response surface methodology

Yan GUO, Chuanfu WU, Qunhui WANG, Min YANG, Qiqi HUANG, Markus MAGEP, Tianlong ZHENG

期刊论文

Optimization of thread partitioning parameters in speculative multithreading based on artificial immune

Yu-xiang LI,Yin-liang ZHAO,Bin LIU,Shuo JI

期刊论文

Intelligent methods for the process parameter determination of plastic injection molding

Huang GAO, Yun ZHANG, Xundao ZHOU, Dequn LI

期刊论文