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Advanced optimization of gas turbine aero-engine transient performance using linkage-learning genetic algorithm:PartⅡ,optimization in flight mission and controller gains correlation development

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Chinese Journal of Aeronautics 2021年第4期34卷 568-588页

作者： Yinfeng LIU Soheil JAFARI Theoklis NIKOLAIDIS Aero Engine Test Department of Hunan Aviation Powerplant Research Institute AECCZhuzhou 412002China Centre for Propulsion Engineering School of Aerospace Transport and Manufacturing(SATM)Cranfield UniversityCranfield MK430ALUK

PartⅠhas illustrated the procedures to apply the Linkage Learning Genetic Algorithm(LLGA)in Gas Turbine Engine(GTE)controller gains tuning and generated the optimization results for runway conditions from idle to ***,the total pressure and temperature of the engine inlet vary as the changing of altitude and Mach number,which would lead to the variation in fuel flow supply *** a result,the optimized gains in runway might not be suitable for other flight *** order to maintain the optimal control performance,the GTE controller gains should be adjusted according to the flight *** paper extends the application of the LLGA method to other flight conditions and then simulates a complete flight mission with different gains and weather condition *** this purpose,the control parameters in the Simulink model of the GTE controller are first corrected by the weather condition in ***,a typical flight mission is defined and divided into different flight segments based on the altitude and Mach number *** representative point is selected from each segment as the datum point for optimization *** this step,the LLGA method is used to find the best gains combinations for different flight conditions and the differences in optimization effects for different flight conditions are analyzed *** simulation results show that the optimization effect of the control performance of each flight condition is dependent on the value of(θδ)~(1/2)and the optimal K_(pla)in some flight conditions is approximately equal to p hd times of the Kplavalue in sea level standard ***,the complete flight mission is simulated with different gains and weather condition *** simulation results show that the engine performance has been greatly improved after optimization by LLGA in the transient state and the high altitude *** other steady states,the optimization effect is not

关键词： Aeroengine control Control optimization Flight condition Flight mission simulation GA GTE LLGA Min-Max controller Robustness

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Profit Guided or Statistical Error Guided? A Study of Stock Index Forecasting Using Support Vector Regression

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Journal of Systems Science & Complexity 2017年第6期30卷 1425-1442页

作者： HU Zhongyi BAO Yukun CHIONG Raymond XIONG Tao school of Information management Wuhan University school of management Huazhong University of Science and Technology school of Electrical Engineering and Computing The University of Newcastle College of Economics and management Huazhong Agricultural University

Stock index forecasting has been one of the most widely investigated topics in the field of financial forecasting. Related studies typically advocate for tuning the parameters of forecasting models by minimizing learning errors measured using statistical metrics such as the mean squared error or mean absolute percentage error. The authors argue that statistical metrics used to guide parameter tuning of forecasting models may not be meaningful, given the fact that the ultimate goal of forecasting is to facilitate investment decisions with expected profits in the future. The authors therefore introduce the Sharpe ratio into the process of model building and take it as the profit metric to guide parameter tuning rather than using the commonly adopted statistical metrics. The authors consider three widely used trading strategies, which include a na¨?ve strategy, a filter strategy and a dual moving average strategy, as investment scenarios. To verify the effectiveness of the proposed profit guided approach, the authors carry out simulation experiments using three global mainstream stock market indices. The results show that profit guided forecasting models are competitive, and in many cases produce significantly better performances than statistical error guided models. This implies thatprofit guided stock index forecasting is a worthwhile alternative over traditional stock index forecasting practices.

关键词： Financial market investment trading strategy parameter optimization stock index forecasting support vector regression

Combining biological denitrification and electricity generation in methane-powered microbial fuel cells

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Journal of Environmental Sciences 2023年第8期130卷 212-222页

作者： Linpeng Yu Eryi Zhang Lin Yang Shiqi Liu Christopher Rensing Shungui Zhou Resources and Environment Fujian Agriculture and Forestry UniversityFuzhou 350002China cranfield University CranfieldBedfordshire MK43 OALUK Biofuels Institute School of Environment and Safety EngineeringJiangsu UniversityZhenjiang 212013China

Methane has been demonstrated to be a feasible substrate for electricity generation in microbial fuel cells(MFCs)and denitrifying anaerobic methane oxidation(DAMO).However,these two processes were evaluated separately in previous studies and it has remained unknown whether methane is able to simultaneously drive these *** we investigated the co-occurrence and performance of these two processes in the anodic chamber of *** results showed that methane successfully fueled both electrogenesis and ***,the maximum nitrate removal rate was significantly enhanced from(1.4±0.8)to(18.4±1.2)mg N/(L·day)by an electrogenic *** the presence of DAMO,the MFCs achieved a maximum voltage of 610 mV and a maximum power density of 143±12 mW/m^(2).Electrochemical analyses demonstrated that some redox substances(***)were likely involved in electrogenesis and also in the denitrification ***-throughput sequencing indicated that the methanogen Methanobacterium,a close relative of Methanobacterium espanolae,catalyzed methane oxidation and cooperated with both exoelectrogens and denitrifiers(e.g.,Azoarcus).This work provides an effective strategy for improving DAMO in methane-powered MFCs,and suggests that methanogens and denitrifiers may jointly be able to provide an alternative to archaeal DAMO for methane-dependent denitrification.

关键词： Anaerobic methane oxidation Denitrification Microbial fuel cells Electricity generation Electroactive compounds Methanobacterium

Hybrid customer requirements rating method for customer-oriented product design using QFD

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Journal of Systems Engineering and Electronics 2015年第3期26卷 533-543页

作者： Fang Wang Hua Li Aijun Liu Xiao Zhang school of Economics and management Xidian University

Quality function deployment （QFD） is a well-known customer-oriented product design methodology. Rating the final importance of customer requirements （CRs） is really a very es- sential starting point in the implementation of QFD, since it largely affects the target setting value of design requirements. This pa- per aims to propose a novel method to deal with the relative importance ratings （RIRs） of CRs problem considering customers＇ diversified requirements and unknown information on customers＇ weights, which is an indispensable process for determining the final importance ratings of CRs. First, a new concept of customer＇s assessment structure is proposed according to the basic idea of grey relational analysis （GRA）, and then a constrained nonlinear optimization model is constructed to describe the assessment information aggregation factors of CRs considering customers＇ personalized and diversified requirements. Furthermore, an im- mune particle swarm optimization （IPSO） algorithm is designed to solve the model, and the weight vector of customers is obtained. Finally, a car door design example is introduced to illustrate the novel hybrid GRA-IPSO method＇s potential application in deter- mining the RIRs of CRs.

关键词： quality function deployment (QFD) customer requirement (CR) grey relational analysis (GRA) mass customization(MC) immune particle swarm optimization (IPSO).

On-Line Scheduling on Parallel Machines to Minimize the Makespan

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Journal of Systems Science & Complexity 2016年第2期29卷 472-477页

作者： LI Songsong ZHANG Yuzhong school of management Qufu Normal University

This paper considers two parallel machine scheduling problems, where the objectives of both problems are to minimize the makespan, and the jobs arrive over time, on two uniform machines with speeds 1 and s （s 〉 1）, and on m identical machines, respectively. For the first problem, the authors show that the on-line LPT algorithm has a competitive ratio of （1 ＋ √5）/2 ≈ 1.6180 and the bound is tight. Furthermore, the authors prove that the on-line LPT algorithm has the best possible competitive ratio if s ≥ 1.8020. For the second problem, the authors present a lower bound of （15 - √17）/8 ≈ 1.3596 on the competitive ratio of any deterministic on-line algorithm. This improves a previous result of 1.3473.

关键词： Lower bound on-line algorithm scheduling.

How Does Debt Structure Influence Stock Price Crash Risk?

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Journal of Systems Science & Complexity 2018年第2期31卷 473-492页

作者： JIA Zichao DENG Lu XU Ruiyang school of Economics and management BeiHang University

This paper uses the financial data of Chinese listed firms to explore the relationship between the debt structure, which is measured as the ratio of trade credit to bank loan, and future stock price crash risk. The empirical results show that the ratio of trade credit to bank loan is positively associated with the firm-specific crash risk while a good institutional environment reduces this positive relationship. In addition, considering the firm＇s ownership type, the authors find that the positive relationship between the debt structure and crash risk is more significant in the SOEs.

关键词： Bank loan crash risk debt structure trade credit.

Water quality assessment in Qu River based on fuzzy water pollution index method

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Journal of Environmental Sciences 2016年第12期28卷 87-92页

作者： Ranran Li Zhihong Zou Yan An school of Economics and management Beihang University

A fuzzy improved water pollution index was proposed based on fuzzy inference system and water pollution index. This method can not only give a comprehensive water quality rank, but also describe the water quality situation with a quantitative value, which is convenient for the water quality comparison between the same ranks. This proposed method is used to assess water quality of Qu River in Sichuan, China. Data used in the assessment were collected from four monitoring stations from 2006 to 2010. The assessment results show that Qu River water quality presents a downward trend and the overall water quality in 2010 is the worst. The spatial variation indicates that water quality of Nanbashequ section is the pessimal. For the sake of comparison, fuzzy comprehensive evaluation and grey relational method were also employed to assess water quality of Qu River. The comparisons of these three approaches＇ assessment results show that the proposed method is reliable.

关键词： Water quality assessmentFuzzy inferenceWater pollution indexFuzzy comprehensive evaluation

Forecasting of dissolved oxygen in the Guanting reservoir using an optimized NGBM(1,1) model

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Journal of Environmental Sciences 2015年第3期27卷 158-164页

作者： Yan An Zhihong Zou Yanfei Zhao school of Economics and management Beihang University

An optimized nonlinear grey Bernoulli model was proposed by using a particle swarm optimization algorithm to solve the parameter optimization problem. In addition, each item in the first-order accumulated generating sequence was set in turn as an initial condition to determine which alternative would yield the highest forecasting accuracy. To test the forecasting performance, the optimized models with different initial conditions were then used to simulate dissolved oxygen concentrations in the Guantlng reservoir inlet and outlet （China）. The empirical results show that the optimized model can remarkably improve forecasting accuracy, and the particle swarm optimization technique is a good tool to solve parameter optimization problems. What＇s more, the optimized model with an initial condition that performs well in in-sample simulation may not do as well as in out-of-sample forecasting.

关键词： Water quality forecasting Dissolved oxygen Nonlinear grey Bernoulli model Particle swarm optimization Initial condition

B2B MARKET FORMATION AND WELFARE IMPLICATION IN A BUYER'S MARKET

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Journal of Systems Science and Systems Engineering 2014年第4期23卷 404-414页

作者： Zhong Wen Jieyuan Wang school of Economics and management Tsinghua University

The emergence of B2B electronic markets has greatly changed the relative bargaining power of buyers and *** study the equilibrium market structure in a buyer＇s *** find that buyer-controlled B2B markets and neutral B2B markets have different equilibrium structures,and the emergence of B2B markets will increase social welfare,but its effect on buyers and sellers will be different：B2B markets increase the consumer surplus of the end market,but their effects on buyer and seller profits are moderated by the relative bargaining power of buyers and *** profits of the side with much weaker bargaining power will decrease due to the introduction of B2B markets.

关键词： B2B market e-commerce social welfare game theory