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Applying Optimized Support Vector Regression Models for Prediction of Tunnel Boring Machine Performance

GEOTECHNICAL AND GEOLOGICAL ENGINEERING 2017年第5期35卷 2205-2217页

作者： Fattahi, Hadi Babanouri, Nima Arak Univ Technol Dept Min Engn Arak Iran Hamedan Univ Technol Dept Min Engn Hamadan Iran

One of the main factors in the effective application of a tunnel boring machine (TBM) is the ability to accurately estimate the machine performance in order to determine the project costs and schedule. Predicting the TBM performance is a nonlinear and multivariable complex problem. The aim of this study is to predict the performance of TBM using the hybrid of support vector regression (SVR) and the differential evolution algorithm (DE), artificial bee colony algorithm (ABC), and gravitational search algorithm (GSA). The DE, ABC and GSA are combined with the SVR for determining the optimal value of its user defined parameters. The optimization implementation by the DE, ABC and GSA significantly improves the generalization ability of the SVR. The uniaxial compressive strength (UCS), average distance between planes of weakness (DPW), the angle between tunnel axis and the planes of weakness (alpha), and intact rock brittleness (BI) were considered as the input parameters, while the rate of penetration was the output parameter. The prediction models were applied to the available data given in the literature, and their performance was assessed based on statistical criteria. The results clearly show the superiority of DE when integrated with SVR for optimizing values of its parameters. In addition, the suggested model was compared with the methods previously presented for predicting the TBM penetration rate. The comparative results revealed that the hybrid of DE and SVR yields a robust model which outperforms other models in terms of the higher correlation coefficient and lower mean squared error.

关键词： Tunnel boring machine Penetration rate Support vector regression differential evolution algorithm Artificial bee colony algorithm Gravitational search algorithm

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Robust Parameter Design and Analysis of a Leaf Compliant Joint for Micropositioning Systems

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ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING 2017年第11期42卷 4811-4823页

作者： Ngoc Le Chau Van Anh Dang Hieu Giang Le Thanh-Phong Dao Ind Univ Ho Chi Minh City Fac Mech Engn Ho Chi Minh City Vietnam Ho Chi Minh City Univ Technol & Educ Fac Mech Engn Ho Chi Minh City Vietnam Ton Duc Thang Univ Div Computat Mechatron Inst Computat Sci Ho Chi Minh City Vietnam Ton Duc Thang Univ Fac Elect & Elect Engn Ho Chi Minh City Vietnam

A compliant joint is used to store and transfer the elastic energy for flexure-based mechanisms. This paper proposes a robust parameter design and analysis for a leaf compliant joint. The joint can achieve a large working travel in the micrometer range. The sensitivity of length l, width w, thickness t and filleted radius r of the joint on the responses are analyzed via finite element method. The parasitic error, dynamics and stiffness are then described. In addition, the stiffness of the joint is reinforced via embedded the silicone rubber into the cavity. Subsequently, the robust optimization of parameters is conducted via the Taguchi method. Analysis of variance is used to determine the effect degree of each parameter. To solve the continuous optimization problem, the second optimization is carried out by integrating of the response surface methodology and differential evolution algorithm. Compared with the genetic algorithm, the proposed optimization method has a faster convergence. The experimental validation is performed to measure the displacement of the joint. The results indicated that the joint can achieve the displacement up to 140.93 mu m. The proposed hybrid optimization algorithm can improve the performance of the leaf compliant joint. The proposed joint can be used for the micro-indentation device for testing the micromechanical properties of micro-sized materials. It can be also developed for biomedical rehabilitation devices to assist disable people.

关键词： Compliant mechanism Flexure joint Parasitic error Silicone rubber Taguchi method Response surface methodology differential evolution algorithm

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Trajectory optimization for solar sail in cislunar navigation constellation with minimal lightness number

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AEROSPACE SCIENCE AND TECHNOLOGY 2017年 70卷 559-567页

作者： Pan, Xiao Xu, Ming Santos, Ramil Beihang Univ Sch Astronaut Beijing 100191 Peoples R China

In view of the limitations of the existing libration-point satellite navigation systems in cislunar space, this paper replaces satellites with solar sails to construct a cislunar navigation constellation and is devoted to the trajectory optimization of solar sails to minimize the lightness number control. The Artificial Lagrangian Points (ALPS) yielded by solar sail in the Sun-Earth+Moon system benefit from the advantages of numberless equilibria and out-of-plane displacement, when compared with the classical Lagrangian points. Limited to the manufacturing of sail film in practice, the candidate constellation architecture in the shape of a cube is constructed based on the optimization of the average lightness number required at ALPs. Considering the lunar gravity, the Hamiltonian-structure-preserving (HSP) controller achieved by changing the sail's attitude and lightness number is developed to stabilize the sails' trajectories near the ALPs. Moreover, an optimal quasi-periodic trajectory with minimum lightness number control is searched for through differential evolution algorithm evolving the controller gains and initial states of orbits. There are three important contributions of the trajectory optimization for a sail in the cislunar navigation constellation: firstly, the large amounts of ALPs break the restrictions on the number and plane of the five classical Lagrangian equilibrium solutions to enlarge the selection of constellations;secondly, the station keeping tool HSP controller powerfully ensures the boundedness of the ALP's trajectory;thirdly, using the optimization algorithm to generate ALP orbits effectively avoids the time consumption of differential correction, which is more convenient and general for the natural trajectory design of ALPs. (C) 2017 Elsevier Masson SAS. All rights reserved.

关键词： Cislunar navigation Trajectory optimization Hamiltonian-structure-preserving controller differential evolution algorithm

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A univariate marginal distribution algorithm based on extreme elitism and its application to the robotic inverse displacement problem

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GENETIC PROGRAMMING AND EVOLVABLE MACHINES 2017年第3期18卷 283-312页

作者： Gao, Shujun de Silva, Clarence W. Univ British Columbia Dept Mech Engn Ind Automat Lab 6250 Appl Sci Lane Vancouver BC V6T 1Z4 Canada

In this paper, a univariate marginal distribution algorithm in continuous domain (UMDA (C) ) based on extreme elitism (EEUMDA (C) ) is proposed for solving the inverse displacement problem (IDP) of robotic manipulators. This algorithm highlights the effect of a few top best solutions to form a primary evolution direction and obtains a fast convergence rate. Then it is implemented to determine the IDP of a 4-degree-of-freedom (DOF) Barrett WAM robotic arm. After that, the algorithm is combined with differential evolution (EEUMDA (C) -DE) to solve the IDP of a 7-DOF Barrett WAM robotic arm. In addition, three other heuristic optimization algorithms (enhanced leader particle swarm optimization, intersect mutation differential evolution, and evolution strategies) are applied to find the IDP solution of the 7-DOF arm and their performance is compared with that of EEUMDA (C) -DE.

关键词： Univariate marginal distribution algorithm Inverse displacement problem Top best solutions Gaussian model differential evolution algorithm

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A differential evolution-based model to estimate the software services development effort

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JOURNAL OF SOFTWARE-evolution AND PROCESS 2016年第1期28卷 57-77页

作者： Bardsiri, Amid Khatibi Hashemi, Seyyed Mohsen Islamic Azad Univ Sci & Res Branch Dept Comp Engn Tehran Iran Islamic Azad Univ Sci & Res Branch Tehran Iran

Accurate estimation of software service development effort is a great challenge both in industry and for academia. The concept of effort is an important and effective parameter in process development and software service management. The reliable estimation of effort helps the project managers to allocate the resources better and manage cost and time so that the project will be finished in the determined time and budget. One of the most popular effort estimation methods is analogy-based estimation (ABE) to compare a service with similar historical cases. Unfortunately, ABE is not capable of generating accurate results unless determining weights for service features. Therefore, this paper aims to make an efficient and reliable model through combining ABE method and differential evolution algorithm to estimate the software services development effort. In fact, the differential evolution algorithm was utilized for weighing features in the similarity function of the ABE method. This weighing process could help determining the importance level of the various service features and extracting the best similar historical case. The proposed hybrid model has been evaluated on two real datasets and two artificial datasets. The obtained results were compared with common effort estimation methods. This comparison showed more accuracy, faster convergence, and lower cost of the proposed model. Copyright (c) 2015 John Wiley & Sons, Ltd.

关键词： development effort analogy based estimation software services differential evolution algorithm

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differential evolution algorithm for emission constrained economic power dispatch problem

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ELECTRIC POWER SYSTEMS RESEARCH 2010年第10期80卷 1286-1292页

作者： Abou El Ela, A. A. Abido, M. A. Spea, S. R. Menoufiya Univ Fac Engn Dept Elect Engn Menoufia Egypt King Fahd Univ Petr & Minerals Dept Elect Engn Dhahran Saudi Arabia

In this paper, a differential evolution (DE) algorithm is developed to solve emission constrained economic power dispatch (ECEPD) problem. Traditionally electric power systems are operated in such a way that the total fuel cost is minimized regardless of emissions produced. With increased requirements for environmental protection, alternative strategies are required. The proposed algorithm attempts to reduce the production of atmospheric emissions such as sulfur oxides and nitrogen oxides, caused by the operation of fossil-fueled thermal generation. Such reduction is achieved by including emissions as a constraint in the objective of the overall dispatching problem. A simple constraint approach to handle the system constraints is proposed. The performance of the proposed algorithm is tested on standard IEEE 30-bus system and is compared with conventional methods. The results obtained demonstrate the effectiveness of the proposed algorithm for solving the emission constrained economic power dispatch problem. Published by Elsevier B.V.

关键词： Economic power dispatch differential evolution algorithm Fuel cost minimization Emission constraint Environmental issues

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Time series forecasting for building energy consumption using weighted Support Vector Regression with differential evolution optimization technique

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ENERGY AND BUILDINGS 2016年 126卷 94-103页

作者： Zhang, Fan Deb, Chirag Lee, Siew Eang Yang, Junjing Shah, Kwok Wei Natl Univ Singapore Inst Syst Sci Singapore 119615 Singapore Natl Univ Singapore Sch Design & Environm Dept Bldg Singapore 117566 Singapore

Electricity load forecasting is crucial for effective operation and management of buildings. Support Vector Regression (SVR) have been successfully used in solving nonlinear regression and time series problems related to building energy consumption forecasting. As the performance of SVR heavily depends on the selection of its parameters, differential evolution (DE) algorithm is employed in this study to solve this problem. The forecasting model is developed using weighted SVR models with nu-SVR and epsilon-SVR. The DE algorithm is again used to determine the weights corresponding to each model. A case of time series energy consumption data from an institutional building in Singapore is used to elucidate the performance of the proposed model. The proposed model can be used to forecast both, half-hourly and daily electricity consumption time series data for the same building. The results show that for half-hourly data, the model exhibits higher weight for nu-SVR, whereas for daily data, a higher weight for epsilon-SVR is observed. The mean absolute percentage error (MAPE) for daily energy consumption data is 5.843 and that for half-hourly energy consumption is 3.767 respectively. A detailed comparison with other evolutionary algorithms show that the proposed model yields higher accuracy for building energy consumption forecasting. (C) 2016 Elsevier B.V. All rights reserved.

关键词： Building energy consumption Energy forecasting Support vector regression differential evolution algorithm Institutional building

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INCREASING THE EFFICIENCY OF CHEBYSHEV SEGMENT FRACTIONAL RATIONAL APPROXIMATION

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CYBERNETICS AND SYSTEMS ANALYSIS 2017年第5期53卷 759-765页

作者： Vakal, L. P. Kalenchuk-Porkhanova, A. A. Vakal, E. S. Natl Acad Sci Ukraine VM Glushkov Inst Cybernet Kiev Ukraine Taras Shevchenko Natl Univ Kyiv Kiev Ukraine

An algorithm for Chebyshev segment approximation with free nodes is presented. Fractional rational functions are used as approximating functions on subintervals. The differential evolution algorithm is used to find op... 详细信息

关键词： Chebyshev segment approximation multidimensional nonlinear optimization problem rational fractions optimal node differential evolution algorithm

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Application of differential evolution for Wind Turbine Micrositing

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MEHRAN UNIVERSITY RESEARCH JOURNAL OF ENGINEERING AND TECHNOLOGY 2017年第2期36卷 353-366页

作者： Massan, Shafiq-Ur-Rehman Wagan, Asim Imdad Shaikh, Muhammad Mujtaba Shah, Muhammad Saleh Shaheed Zulfikar Ali Bhutto Inst Sci & Technol Karachi Pakistan Mohammad Ali Jinnah Univ Karachi Pakistan Mehran Univ Engn & Technol Dept Basic Sci & Related Studies Jamshoro Pakistan Govt Saifee Zahabi Edhi Coll Educ Karachi Pakistan

WTM (Wind Turbine Micrositing) has been an important topic of discussion in recent times. A number of evolutionary algorithms have been applied to the WTM problem. The DEA (differential evolution algorithm) is used for a bi-constrained optimization for getting maximum power production at the least cost from a 2x2 km space. It is shown that the DEA performs comparably to the GA (Genetic algorithms) for wind farm optimization. The optimal configuration obtained enlists the number of turbines, the cost of power generated as well as the power produced. Moreover, this study is augmented by comparison with past approaches by using the GA for the same purpose.

关键词： Wind Turbine Micro-Siting N.O. Jensen Model Heuristics Wind Turbine Optimization differential evolution algorithm Geneticalgorithm

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Temperature prediction model of two-layer cascade control industrial furnace based on PFC-FLC-DE

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JOURNAL OF COMPUTATIONAL METHODS IN SCIENCES AND ENGINEERING 2017年第3期17卷 481-495页

作者： Peng, XiaoHong Xie, Shiyi Chen, Liang Wang, DongYa Guangdong Ocean Univ Zhanjiang Guangdong Peoples R China

In view of the large lag of industrial furnace temperature, serious nonlinear, high order model, etc., we proposed a temperature prediction and control model of a joint two-layer, in which the PFC was taken as the supervisory layer, and the fuzzy logic control, FLC for short, was taken as the control layer. The model combines the advantages of PFC and FLC. The upper layer is to realize the advance regulation by using predictive functional control (PFC) to forecast the deviation of the system, and the lower layer is to realize fuel flow and air flow control by using the cascade fuzzy controller. The cascade fuzzy controller can handle multiple process control parameters, greatly reducing the number of fuzzy rules;and by using differential evolution algorithm (DE) to optimize the quantization factor and scaling factor of the membership function of fuzzy controller, which greatly improve the accuracy of prediction. After utilizing this model to process the control analyses of polystyrene industrial furnace temperature in a petrochemical enterprise in Zhanjiang, the result shows that the model has the advantages of fast tracking, accurate control, no overload and so on. The control effect is better than that of the fuzzy neural network control and the conventional PID control method.

关键词： Predictive functional control fuzzy logic control differential evolution algorithm industrial furnace temperature control

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