检索结果-内蒙古大学图书馆

Multi-period portfolio optimization using coherent fuzzy numbers in a credibilistic environment

EXPERT SYSTEMS WITH APPLICATIONS 2021年 167卷 114135-114135页

作者： Gupta, Pankaj Mehlawat, Mukesh Kumar Khan, Ahmad Zaman Univ Delhi Dept Operat Res Delhi 110007 India

In this paper, we use an extension of fuzzy numbers, called coherent fuzzy numbers, to model asset returns and an investor's perception of the stock market (pessimistic, optimistic, or neutral) simultaneously. Two multi-period multi-objective portfolio optimization models are formulated using mean absolute semi-deviation and Conditional Value-at-Risk (CVaR) as risk measures, respectively. We aim to provide more flexibility to the investor in specifying the risk tolerance and devise optimum investment plans for different investment horizons. The proposed models also incorporate bound, cardinality, and skewness constraints for each investment period to capture various stock market scenarios. A real-coded genetic algorithm is employed to solve the resultant models. Two real-life case studies involving 20 assets of the National Stock Exchange (NSE), India, and another involving 50 assets listed in the S&P 500 and NASDAQ-100 indexes have been provided to illustrate the efficacy and advantages of the models. An in-sample and out-of-sample analysis have been done for both the models to analyze the performance in the real-world scenario. The conclusion drawn from the analysis strongly emphasizes on accurately assessing the current stock market prospects, i.e., adopting the right attitude (pessimistic, optimistic, or neutral), is of paramount importance and must be included in the portfolio optimization problem.

关键词： Fuzzy multi-period portfolio optimization Multi-objective programming Fuzzy set theory Coherent fuzzy numbers Conditional Value-at-Risk real-coded genetic algorithm

来源：评论

学校读者我要写书评

暂无评论

An approach for design optimization of helical gear pair with balanced specific sliding and modified tooth profile

引用

STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION 2019年第1期60卷 331-341页

作者： Rai, Paridhi Barman, Asim Gopal Natl Inst Technol Patna Dept Mech Engn Patna Bihar India

A unique perspective in design optimization of helical gear pair has been emerged and presented in this article. Specific sliding needs to be balanced for enhancing wear and scuffing resistance of helical gears. Optimized modification in tooth profile has immense benefits in gear operations. Effect of profile shift and specific sliding on design optimization of helical gear pair have been studied and found to be beneficial of great importance. Preventing undercutting, balancing of wear and bending fatigue strength and centre distance adjustment are some of the advantages of profile tooth modifications. real-coded genetic algorithm (RCGA) has been used to attain minimum volume of helical gear pair. Profile shift coefficients for gear and pinion have been included as design variables along with mostly used generic design variables, module, face width and number of teeth on pinion. Specific sliding, transverse contact ratio and face width constraint along with other strength requirements are the design constraints. The optimal design solutions obtained with and without profile shift are recorded and compared with commercially used software for validation. 3D computer-aided design (CAD) models have been developed by using the optimized results obtained from RCGA and commercially used software. These CAD models are used for performing finite element analysis (FEA) on the helical gear set for analyzing the stress developed in the gear pair. The developed stress in the helical gear pair is found to be well within the allowable stress limits for the gear pair.

关键词： Helical gear Profile shift Specific sliding Volume optimization real-coded genetic algorithm FEM analysis

来源：评论

学校读者我要写书评

暂无评论

Optimal operation of the combined heat and power system equipped with power-to-heat devices for the improvement of wind energy utilization

引用

ENERGY SCIENCE & ENGINEERING 2019年第5期7卷 1605-1620页

作者： Yu, Yanjuan Chen, Hongkun Chen, Lei Chen, Cheng Wu, Jun Wuhan Univ Sch Elect Engn & Automat 8 Donghu South Rd Wuhan Hubei Peoples R China

The combined heat and power system (CHPS) is one important type of the integrated energy system in Northern China. Compared with the independently operated power system, the combined heat and power system (CHPS) has a great potential to improve the utilization of wind energy in virtue of the energy storage of the heating system and power-to-heat (P2H) devices. This paper studies the optimal operation of the CHPS equipped with the electric boiler (EB) and heat pump (HP). Comprehensive factors are considered, including P2H conversion, the thermal inertia of district heating network (DHN) and buildings, and adjustable heat loads. An equivalent model of the heating system is developed to express the direct mathematical relations between the heat source and heat loads. Redundant details of the DHN are simplified to reduce the complexity of the optimization problem. Furthermore, a self-repair method incorporated with the real-coded genetic algorithm (RCGA) is proposed to efficiently handle the nonlinear constraints. The effectiveness of the solving method is verified in case studies. The impacts of the EB and the HP on the CHPS are compared in details. The results show that the HP offers better performance than the EB on coal saving and improving wind power integration.

关键词： combined heat and power system power-to-heat device real-coded genetic algorithm wind power integration

来源：评论

学校读者我要写书评

暂无评论

A directional crossover (DX) operator for real parameter optimization using genetic algorithm

引用

APPLIED INTELLIGENCE 2019年第5期49卷 1841-1865页

作者： Das, Amit Kumar Pratihar, Dilip Kumar Indian Inst Technol Kharagpur Dept Mech Engn Kharagpur 721302 W Bengal India

Nature-inspired optimization algorithms have received more and more attention from the researchers due to their several advantages. genetic algorithm (GA) is one of such bio-inspired optimization techniques, which has mainly three operators, namely selection, crossover, and mutation. Several attempts had been made to make these operators of a GA more efficient in terms of performance and convergence rates. In this paper, a directional crossover (DX) has been proposed for a real-coded genetic algorithm (RGA). As the name suggests, this proposed DX uses the directional information of the search process for creating the children solutions. Moreover, one method has been suggested to obtain this directional information for identifying the most promising areas of the variable space. To measure the performance of an RGA with the proposed crossover operator (DX), experiments are carried out on a set of six popular optimization functions, and the obtained results have been compared to that yielded by the RGAs with other well-known crossover operators. RGA with the proposed DX operator (RGA-DX) has outperformed the other ones, and the same has been confirmed through the statistical analyses. In addition, the performance of the RGA-DX has been compared to that of other five recently proposed optimization techniques on the six test functions and one constrained optimization problem. In these performance comparisons also, the RGA-DX has outperformed the other ones. Therefore, in all the experiments, RGA-DX has been found to yield the better quality of solutions with the faster convergence rate.

关键词： Evolutionary algorithm real-coded genetic algorithm Directional crossover Exponential crossover Convergence rate

来源：评论

学校读者我要写书评

暂无评论

Wind Farm Layout Optimization with a Novel Gaussian Wake Model

Wind Farm Layout Optimization with a Novel Gaussian Wake Mod...

引用

IEEE International Conference on Industrial Technology (IEEE ICIT)

作者： Tao, Siyu Xu, Qingshan Zhou, Changcheng Zhou, Jiemin Zheng, Gang Southeast Univ Dept Elect Engn Nanjing Jiangsu Peoples R China China Southern Power Grid Elect Power Res Inst Guangzhou Guangdong Peoples R China Nanjing Univ Aeronaut & Astronaut Coll Civil Aviat Nanjing Jiangsu Peoples R China

ISBN: (纸本)9781538663769

This work proposes an optimal wind farm layout framework to obtain the optimal placement of wind turbines in a wind farm. The optimization objective is to minimize the average cost per net electric power generated by a wind farm with a fixed number of turbines while the distance between turbines is no less than the allowed minimal distance in the far wake region. The wind farm micro-siting problem with Frandsen's Gaussian wake model based on the conservation of momentum is formulated as a constrained optimization problem and solved by real-coded genetic algorithm. Simulation results demonstrate that the Frandsen's Gaussain wake model is more consistent with real wakes and thus the optimization result is more accurate than the existing practices.

关键词： wind farm planning wake effect real-coded genetic algorithm Frandsen's model Gaussian distribution model

来源：评论

学校读者我要写书评

暂无评论

Improving Plagiarism Detection Using genetic algorithm 42

Improving Plagiarism Detection Using Genetic Algorithm

引用

42nd International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO)

作者： Pajic, Enil Ljubovic, Vedran Univ Sarajevo Fac Elect Engn Sarajevo Bosnia & Herceg

ISBN: (纸本)9789532330984

Detecting instances of plagiarism in student homework, with program code in particular, is a subject of active research for over 30 years. One of the early proposed methods was extraction and comparison of source-code metrics. Even though this approach has low algorithmic complexity, it is rarely used in recent papers with some authors claiming that better results are obtained using other methods. In this paper, plagiarism detection is treated as an information retrieval problem, specifically query-by-example (QbE). A feature vector is constructed from source metrics and compared using common similarity measures. Further, evolutionary computation methods are used to optimize the similarity measure. It is shown that, by several metrics used, detection results are on par with state-of-the-art methods with significantly lower execution time.

关键词： plagiarism detection real-coded genetic algorithm feature extraction

来源：评论

学校读者我要写书评

暂无评论

Implementation and Evaluation of Grey Wolf Optimization algorithm on Power System Stability Enhancement 10

Implementation and Evaluation of Grey Wolf Optimization Algo...

引用

10th IEEE GCC Conference and Exhibition (GCC)

作者： Alahmed, Ahmed Taiwo, Salman Abido, Mohammed King Fahd Univ Petr & Minerals Elect Engn Dept Dhahran Saudi Arabia KA CARE Energy Res & Innovat Ctr Dhahran Saudi Arabia

ISBN: (纸本)9781538694770

The increasing complexity of today's applications has surfaced the importance of meta-heuristic techniques which can deal with multi-variable, multi-constraints, highly non-linear and non-smooth problems. Their superior performance and immunity of getting trapped in local maxima or minima made them eminent when compared with classical optimization methods, which have several limitations. In this context, implementation and evaluation of Grey Wolf Optimization algorithm (GWOA) on power system stability enhancement will be carried. The objective function is to maximize the minimum damping ratio of the controller to enhance stability and ensure faster damping. The results will be then compared with other evolutionary techniques, particularly real-coded genetic algorithm (RCGA) and Differential Evolution (DE) method. The simulation results will be established using MATLAB.

关键词： Meta-heuristic techniques evolutionary algorithm Grey wolf optimization constrained optimization nature-inspired optimization real-coded genetic algorithm differential evolution method

来源：评论

学校读者我要写书评

暂无评论

Profit maximizing logistic model for customer churn prediction using genetic algorithms

引用

SWARM AND EVOLUTIONARY COMPUTATION 2018年 40卷 116-130页

作者： Stripling, Eugen vanden Broucke, Seppe Antonio, Katrien Baesens, Bart Snoeck, Monique Katholieke Univ Leuven Dept Decis Sci & Informat Management Leuven Belgium Katholieke Univ Leuven Dept Accountancy Finance & Insurance Leuven Belgium Univ Amsterdam Sect Quantitat Econ Amsterdam Netherlands Univ Southampton Sch Management Southampton Hants England

To detect churners in a vast customer base, as is the case with telephone service providers, companies heavily rely on predictive churn models to remain competitive in a saturated market. In previous work, the expected maximum profit measure for customer churn (EMPC) has been proposed in order to determine the most profitable churn model. However, profit concerns are not directly integrated into the model construction. Therefore, we present a classifier, named ProfLogit, that maximizes the EMPC In the training step using a genetic algorithm, where ProfLogit's interior model structure resembles a lasso-regularized logistic model. Additionally, we introduce threshold-independent recall and precision measures based on the expected profit maximizing fraction, which is derived from the EMPC framework. Our proposed technique aims to construct profitable churn models for retention campaigns to satisfy the business requirement of profit maximization. In a benchmark study with nine real-life data sets, ProfLogit exhibits the overall highest, out-of-sample EMPC performance as well as the overall best, profit-based precision and recall values. As a result of the lasso resemblance, ProfLogit also performs a profit-based feature selection in which features are selected that would otherwise be excluded with an accuracy-based measure, which is another noteworthy finding.

关键词： Data mining Customer churn prediction Lasso-regularized logistic regression model Profit-based model evaluation real-coded genetic algorithm

来源：评论

学校读者我要写书评

暂无评论

Optimal design of minimum multiplier lattice wave digital lowpass filter using metaheuristic techniques

引用

IET SIGNAL PROCESSING 2018年第6期12卷 700-712页

作者： Barsainya, Richa Aggarwal, Apoorva Rawat, Tarun Kumar Amity Sch Engn & Technol Dept Elect & Commun Engn New Delhi 110061 India Bharati Vidyapeeths Coll Engn Dept Elect & Elect Engn New Delhi 110063 India Netaji Subhas Inst Technol Dept Elect & Commun Engn New Delhi 110078 India

This study aims towards the efficient design of arbitrary-band and halfband lowpass (LP) filter based on lattice wave digital filter (LWDF) structure with the usage of minimal number of multipliers in its structural realisation. The designing of the LP filter is formulated as an optimisation problem where coefficients of LWDF transfer function are iteratively optimised by the evolutionary algorithms. The potential of four optimisation algorithms, real-coded genetic algorithm, particle swarm optimisation, differential evolution algorithm, and cuckoo search algorithm, are explored for determining the optimal LWDF coefficients by minimising the error objective function. The structural realisation of LP using LWDF structure enhances the design accuracy as the usage of multiplier prominently reduces. The simulation and statistical results of the proposed lattice wave digital lowpass filter (LWDLF) and bireciprocal lattice wave digital lowpass filter (BLWDLF) design show significant improvement in the mean square error, passband ripples, transition bandwidth, stopband attenuation, rate of convergence, and execution time. To manifest the efficient design of the proposed LWDLF and BLWDLF, the results are compared with the designed arbitrary-band, halfband canonic-LP filters and previous published works.

关键词： low-pass filters genetic algorithms particle swarm optimisation search problems digital filters minimum multiplier lattice wave digital lowpass filter halfband lowpass filter arbitrary-band lowpass filter optimisation problem real-coded genetic algorithm particle swarm optimisation differential evolution algorithm cuckoo search algorithm LWDLF BLWDLF

来源：评论

学校读者我要写书评

暂无评论

A new weather-routing system that accounts for ship stability based on a real-coded genetic algorithm

引用

JOURNAL OF MARINE SCIENCE AND TECHNOLOGY 2011年第3期16卷 311-322页

作者： Maki, Atsuo Akimoto, Youhei Nagata, Yuichi Kobayashi, Shigenobu Kobayashi, Eiichi Shiotani, Shigeaki Ohsawa, Teruo Umeda, Naoya Kobe Univ Grad Sch Maritime Sci Higashinada Ku Kobe Hyogo 6580022 Japan Tokyo Inst Technol Interdisciplinary Grad Sch Sci & Engn Yokohama Kanagawa 2268502 Japan Osaka Univ Dept Naval Architecture & Ocean Engn Grad Sch Engn Osaka 5650971 Japan

The operation schedule of an oceangoing vessel can be influenced by wave or wind disturbances, and is therefore weather routed. The weather-routing problem is considered to be a multimodal function problem. Therefore, in the present research, the real-coded genetic algorithm technique (an evolutionary calculation technique) is applied to globally search for the optimum route. Additionally, to avoid maritime accidents due to parametric rolling, this route optimization method takes into account the risk of parametric rolling as one of its objective functions. Numerical verification is carried out for three kinds of objective functions with different weight ratios between fuel efficiency and ship safety in parametric rolling. As a result, it is numerically confirmed that the relation between economics and ship safety is a trade-off, and the safer route is not necessarily the most economical. Considering its robustness, the proposed method appears to be a powerful practical tool by choosing the most appropriate weights for economics and ship safety.

关键词： Weather-routing Ship stability real-coded genetic algorithm

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：