检索结果-内蒙古大学图书馆

A personalized self-learning system based on knowledge graph and differential evolution algorithm

CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE 2022年第8期34卷

作者： Wang, Feng Zhang, Lingling Chen, Xingchen Wang, Ziming Xu, Xin Kunming Univ Sci & Technol Sch Management & Econ Kunming Yunnan Peoples R China Univ Chinese Acad Sci Sch Econ & Management 19A Yuquan Rd Beijing 100049 Peoples R China Univ Chinese Acad Sci Sch Comp Sci & Technol Beijing Peoples R China Chinese Acad Sci Inst Zool Beijing Peoples R China Hong Kong Polytech Univ Dept Management & Mkt Hong Kong Peoples R China

Discovering the most adaptive learning path and content is an urgent issue for nowadays e-learning environment, for achieving learning goals efficiently and effectively. The main challenge of building this system is to provide appropriate educational guide and resource for different learners with respective interests and knowledge base. In order to reduce people's cognitive overload and fulfill their self-learning requirements, this article proposes a framework for a self-learning system. The system is design to be closed and updated automatically, in which learning path is discovered based on differential evolution (DE) algorithm and knowledge graph. The output of the system includes: (1) the personalized learning path adapted to learner's specific needs;(2) learning resource recommendation matching the learning path;(3) test results of learners' learning effect after following the learning path and resources recommendation;(4) revised learning path and resources recommendation according to learner's evaluation. Experimental results show that the system based on DE algorithm and disciplinary knowledge graph is feasible in optimal learning path discovery and further learning resources recommendation.

关键词： differential evolution algorithm knowledge graph learning path self-learning system

来源：评论

学校读者我要写书评

暂无评论

LIDDE: A differential evolution algorithm based on local-influence-descending search strategy for influence maximization in social networks

引用

JOURNAL OF NETWORK AND COMPUTER APPLICATIONS 2021年 178卷 102973-102973页

作者： Qiu, Liqing Tian, Xiangbo Zhang, Jianyi Gu, Chunmei Sai, Shiqi Shandong Univ Sci & Technol Coll Comp Sci & Engn Shandong Prov Key Lab Wisdom Mine Informat Techno 579 Qianwangang Rd Qingdao 266590 Shandong Peoples R China

Influence maximization aims to select k seed nodes from social networks so that the expected number of nodes activated by the seed nodes can be maximized. With the development and popularity of Internet technology, the influence maximization has become a vital problem, especially for viral marketing. However, most existing algorithms utilize the greedy strategy to select seed nodes, which usually leads themselves into local optimal solution. Most other algorithms that not based on the greedy strategy usually have low efficiency. Therefore, a Local-Influence-Descending search strategy is proposed, which can obtain a node set in which each node has relatively large influence. Afterwards, based on this strategy, a new approach for influence maximization is proposed to solve these problems, called Local-Influence-Descending differential evolution (LIDDE). It can improve the accuracy as well as the computation efficiency of influence maximization algorithms based on swarm intelligence. Experimental results on six real-world social networks demonstrate that the proposed algorithm outperforms all comparison algorithms in terms of accuracy and all algorithms based on swarm intelligence in terms of efficiency.

关键词： Social networks Influence maximization differential evolution algorithm Local influence

来源：评论

学校读者我要写书评

暂无评论

Reservoir production optimization based on surrograte model and differential evolution algorithm

引用

JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING 2021年 205卷 108879-108879页

作者： Gu, Jianwei Liu, Wei Zhang, Kai Zhai, Liang Zhang, Yigen Chen, Fuzhen China Univ Petr East China Key Lab Unconvent Oil & Gas Dev Minist Educ Qingdao 266580 Peoples R China China Univ Petr East China Sch Petr Engn Qingdao 266580 Peoples R China Shengli Oil Field Explorat & Dev Res Inst Dongying 257000 Peoples R China

Production Optimization is a significant method for oilfields to control water cut and stabilize oil production. When the oilfield enters the high or ultra-high water cut stage, it becomes particularly important to use production optimization methods for improving the water-flooding efficiency. Currently, the commonly used production optimization methods are based on reservoir simulators. Such methods require lots of forward simulations during optimizing, which results in low computational efficiency. It's not applicable to the reservoir without numerical simulation models. Thus, a new production optimization method based on the reservoir proxy model is proposed in this work. Firstly, the dynamic production data of the oilfield are collected and preprocessed for training the Extreme Gradient Boosting model, and constructing the proxy model for water cut prediction of producers and the reservoir. Then, an optimal control model for minimizing the water cut of the reservoir can be constructed based on the proxy model. Finally, an optimal injection-production scheme can be obtained by using the differential evolution algorithm. For the evaluation and verification purposes, the proposed method is applied to a well block from SL oilfield, China. Empirical results demonstrated that the proposed method can effectively improve the water-flooding efficiency.

关键词： Production optimization Machine learning Proxy model Extreme gradient boosting differential evolution algorithm

来源：评论

学校读者我要写书评

暂无评论

Optimized Tamm-plasmon structure by differential evolution algorithm for single and dual peaks hot-electron photodetection

引用

OPTICAL MATERIALS 2021年 113卷 110857-110857页

作者： Zhou, Chufan Wang, Zhiyu Ho, Ya-Lun Shiomi, Junichiro Delaunay, Jean-Jacques Univ Tokyo Sch Engn Dept Mech Engn Tokyo 1138656 Japan

Wavelength-selective photodetectors with dual and multiple narrowband spectral responses in the infrared range are essential in the development of hyperspectral imaging technology and have attracted great attention due to their potential applications in a variety of areas such as resource remote sensing and mineral exploration. Here, we introduce an efficient optimization of Tamm-plasmon (TP) structure-based hot electron photodetection devices in the telecommunications wavelengths. The devices consist of a Si/SiO2 distributed Bragg reflector (DBR) multilayer structure atop of an Au/n-Si Schottky diode. The DBR structure is optimized using differential evolution (DE) algorithm for wavelength-selectivity and ultra-narrow linewidths at arbitrarily wavelengths. DE shows excellent capability and efficiency in solving a high dimensional continuous optimization problem with competitive speed. The optimized TP structure by DE exhibits near-unity absorptance at the designed wavelengths and requires a relatively short computation time on a standard computer of approximately one and three days to search the optimized TP structures for single and dual absorption peak photodetection, respectively. This result shows that DE is efficient for multilayer structure optimization. Finally, a mechanism for selective photodetection of the two sensitive wavelengths is proposed by tuning the height of the Au/n-Si Schottky barrier with a bias voltage. This wavelength selection mechanism opens the way for dual absorption peaks photodetection.

关键词： Tamm-plasmon differential evolution algorithm Hot-electron photodetection Telecommunication

来源：评论

学校读者我要写书评

暂无评论

Resolving the piezoelectric properties through differential evolution algorithm via piezoresponse force microscopy

引用

INTERNATIONAL JOURNAL OF MECHANICAL SCIENCES 2021年 190卷 106034-106034页

作者： Feng, C. S. Zhu, R. K. Ming, W. J. Pan, K. Peng, J. L. Liu, Y. Y. Lei, C. H. Xiangtan Univ Sch Mat Sci & Engn Key Lab Low Dimens Mat & Applicat Technol Minist Educ Xiangtan 411105 Peoples R China St Louis Univ Dept Aerosp & Mech Engn St Louis MO 63103 USA

Piezoresponse force microscopy (PFM) has rapidly become an important tool for characterizing electromechanical properties in piezoelectric materials at the nanoscale. However, there remains a challenge on the accurate quantitative determination of the piezoelectric coefficients through the electromechanical responses in PFM experiments, due to the long-range electroelastic interactions between the charged scanning probe of the microscopy and piezoelectric mediums. In this paper, differential evolution algorithm (DEA) has been utilized to quantitatively analyze the piezoelectric properties of transversely isotropic piezoelectric mediums via PFM experiment. Considering the coupling between piezoelectric mediums and air, we first extend the fully coupled theory to calculate the electromechanical responses including surface displacements and potentials underneath the probe. We further observe the relations among electromechanical responses, intrinsic piezoelectric properties and measurement conditions, which point us to choose the proper measurement conditions and optimization strategy during the resolving process through DEA. Finally, all the components of the transversely isotropic piezoelectric coefficients are successfully resolved after two-step optimization through the DEA combined with the fully coupled theory. This study provides an important guidance for quantitative and high-throughput determination of the electromechanical properties via PFM experiments.

关键词： Piezoresponse force microscopy (PFM) Piezoelectric materials Electromechanical coupling Optimization differential evolution algorithm

来源：评论

学校读者我要写书评

暂无评论

Efficient Optimization Based differential evolution algorithm for Accurate Rational Function Modeling of Radio-Frequency Filters

引用

JOURNAL OF COMMUNICATIONS TECHNOLOGY AND ELECTRONICS 2021年第SUPPL 2期66卷 S79-S88页

作者： Vrinda, K. Kurup, D. G. Amrita Vishwa Vidyapeetham Dept Elect & Commun Engn Bengaluru 560035 India

The article presents a stochastic population-based optimization algorithm, called differential evolution algorithm, to optimally approximate Radio-Frequency filters into a compact mathematical form consisting of poles and residues. The methodology enables reduced-order rational function models, generated by minimizing a frequency domain least square error function. The article presents numerical examples of various filter prototypes to illustrate the accuracy of the differential evolution algorithm in terms of its system identification capability. The results show that differential evolution algorithm is capable of identifying the poles and residues of filters accurately. It is also observed that differential evolution algorithm approximates the systems with a reduced-order of approximation compared with the existing modeling algorithm. Further, differential evolution algorithm is applied to determine the pole-zero model of a Ka-band waveguide E-Plane Bandpass Filter (EPF). We have observed that the proposed methodology is capable of generating accurate reduced-order rational function models of microwave filters from their frequency domain responses.

关键词： rational function model differential evolution algorithm E-plane filter waveguide radio frequency filters

来源：评论

学校读者我要写书评

暂无评论

A Novel Solution Encoding in the differential evolution algorithm for Optimizing Tourist Trip Design Problems 13th

A Novel Solution Encoding in the Differential Evolution Algo...

引用

13th International Conference on Learning and Intelligent Optimization (LION)

作者： Trachanatzi, Dimitra Rigakis, Manousos Taxidou, Andromachi Marinaki, Magdalene Marinakis, Yannis Matsatsinis, Nikolaos Tech Univ Crete Sch Prod Engn & Management Univ Campus Khania Crete Greece

ISBN: (纸本)9783030386290;9783030386283

In this paper, a tourist trip design problem is simulated by the Capacitated Team Orienteering Problem (CTOP). The objective of the CTOP is to form feasible solution, as a set of itineraries, that represent a sequence visit of nodes, that maximize the total prize collected from them. Each itinerary is constrained by the vehicle capacity and the total travelled time. The proposed algorithmic framework, the Distance Related differential algorithm (DRDE), is a combination of the widely-known differential evolution algorithm (DE) and a novel encoding/decoding process, namely the Distance Related (DR). The process is based on the representation of the solution vector by the Euclidean Distance of the included nodes and offers a data-oriented approach to apply the original DE to a discrete optimization problem, such as the CTOP. The efficiency of the proposed algorithm is demonstrated over computational experiments.

关键词： Capacitated Team Orienteering Problem differential evolution algorithm DR solution encoding

来源：评论

学校读者我要写书评

暂无评论

A novel method of global optimisation for wavefront shaping based on the differential evolution algorithm

引用

OPTICS COMMUNICATIONS 2021年 481卷 126541-126541页

作者： Hua, Yingzi Sui, Xiubao Zhou, Shenghang Chen, Qian Gu, Guohua Bai, Hongyang Li, Wei Nanjing Univ Sci & Technol Sch Elect Engn & Optoelect Technol Nanjing 210094 Peoples R China Nanjing Univ Sci & Technol Sch Energy & Power Nanjing 210094 Peoples R China Peoples Liberat Army China Unit 96037 Baoji 721000 Peoples R China

This paper proposes a novel wavefront-shaping-based focusing method, by introducing the differential evolution algorithm (DEA), thereby realising a faster convergence rate and improved enhancement compared to rival algorithms. Via simulations, we show that our proposed DEA-based approach delivers the best focusing performance irrespective of the influence of noise. Experimental results demonstrate that the DEA boosts the enhancement for an equivalent number of measurements compared with conventional optimisation methods. Furthermore, we reveal the influence of certain DEA parameters, leading to the emergence of many modified DEAs that perform impressively. The proposed DEA-based method simplifies the computational complexity and implementation process of wavefront shaping, offering useful insights for the future study of optimisation algorithms for wavefront shaping, as well as potential for practical applications, such as deep tissue focusing.

关键词： Scattering Focusing Wavefront shaping differential evolution algorithm

来源：评论

学校读者我要写书评

暂无评论

Estimation of Single-Diode Photovoltaic Model Using the differential evolution algorithm with Adaptive Boundaries

引用

ENERGIES 2021年第13期14卷 3925页

作者： Cardenas-Bravo, Carlos Barraza, Rodrigo Sanchez-Squella, Antonio Valdivia-Lefort, Patricio Castillo-Burns, Federico Univ Tecn Federico Santa Maria Dept Elect Engn Santiago 8320000 Chile Univ Tecn Federico Santa Maria Dept Mech Engn Santiago 8320000 Chile

This study proposes a calculation methodology that determines the optimal boundary parameters of the single-diode photovoltaic model. It allows the calculation of the single-diode photovoltaic model when no reference parameter boundaries are available. The differential evolution algorithm, integrated with a step-by-step boundary definition module, is used to calculate the optimal parameters of the single-diode photovoltaic model, improving the performance of the classic algorithm compared with other studies. The solution is validated by comparing the results with well-established algorithms described in the state-of-the-art, and by estimating the five important points (cardinal points) of an IV curve, namely short-circuit, maximum power, and open circuit points, using a database composed of 100 solar photovoltaic modules. The results show that an optimal set of parameter boundaries enables the differential evolution algorithm to minimize the error of the estimated cardinal points. Moreover, the proposed calculus methodology is capable of producing high-performance response photovoltaic models for different technologies and rated powers.

关键词： photovoltaic single-diode model differential evolution algorithm adjustable limits boundaries calculation

来源：评论

学校读者我要写书评

暂无评论

A Darwinian differential evolution algorithm for Multilevel Image Thresholding

引用

INTERNATIONAL JOURNAL OF HUMANOID ROBOTICS 2021年第4期18卷

作者： Ehsaeyan, Ehsan Zolghadrasli, Alireza Shiraz Univ Sch Elect & Comp Engn Shiraz *** Iran

Image segmentation is a prime operation to understand the content of images. Multilevel thresholding is applied in image segmentation because of its speed and accuracy. In this paper, a novel multilevel thresholding algorithm based on differential evolution (DE) search is introduced. One of the major drawbacks of metaheuristic algorithms is the stagnation phenomenon which leads to falling into local optimums and premature convergence. To overcome this shortcoming, the idea of Darwinian theory is incorporated with DE algorithm to increase the diversity and quality of the individuals without decreasing the convergence speed of DE algorithm. A policy of encouragement and punishment is considered to lead searching agents in the search space and reduce the computational time. The algorithm is implemented based on dividing the population into specified groups and each group tries to find a better location. Ten test images are selected to verify the ability of our algorithm using the famous energy curve method. Kapur entropy and Type 2 fuzzy entropy are employed to evaluate the capability of the introduced algorithm. Nine different metaheuristic algorithms with Darwinian modes are also implemented and compared with our method. Experimental results manifest that the proposed method is a powerful tool for multilevel thresholding and the obtained results outperform the DE algorithm and other methods.

关键词： Image segmentation multilevel thresholding differential evolution algorithm Darwinian theory

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：