检索结果-内蒙古大学图书馆

Influencing factors of stock returns based on Fama-French model and intelligent algorithm

SOFT COMPUTING 2023年第14期27卷 10359-10368页

作者： Rui, Xunyuan Tongling Univ Sch Finance Tongling 244000 Anhui Peoples R China

Due to the large number of stock companies, complex stock categories and inconsistent evaluation standards of market value, it is not conducive to the choice of investors. Based on the theory and practice of traditional stock performance evaluation model, this paper integrates the algorithm thought structure of Fama-French five-factor model and proposes a machine learning algorithm model for stock performance research. In addition, this paper also builds a model that can evaluate the style and timing ability of fund managers to improve the fund performance evaluation system to a greater extent. With the help of the performance evaluation updating function of the model, it provides a new experience material in the empirical research composition of the fund performance field. In the system test module, the former prediction data and the actual experimental data are integrated, and the two are sorted out and compared, which proves the feasibility and effectiveness of the proposed algorithm model. The final experimental results verify the usefulness of the model in stock return prediction and analysis of influencing factors.

关键词： Fama-French model intelligent algorithm Stock returns Influencing factors

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EdgeVCD: intelligent algorithm-Inspired Content Distribution in Vehicular Edge Computing Network

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IEEE INTERNET OF THINGS JOURNAL 2020年第6期7卷 5562-5579页

作者： Luo, Quyuan Li, Changle Luan, Tom H. Shi, Weisong Xidian Univ State Key Lab Integrated Serv Networks Xian 710071 Peoples R China Xidian Univ Sch Cyber Engn Xian 710071 Peoples R China Wayne State Univ Dept Comp Sci Detroit MI 48202 USA

Vehicular edge computing (VEC), which integrates mobile-edge computing (MEC) into vehicular networks, can provide more capability for executing resource-hungry applications and lower latency for connected vehicles. Distributing the result content to connected vehicles is vital for them to take proper actions based on computing results. However, the increasing number of connected vehicles and the limited communication resources make the content distribution a challenge. Besides, the diversity of connected vehicles and contents makes it more challenging for content distribution. To address this issue, in this article, we propose EdgeVCD, an intelligent algorithm-inspired content distribution scheme. Specifically, we first propose a dual-importance (DI) evaluation approach to reflect the relationship between the Priority of Vehicles (PoV) and the Priority of Contents (PoC). To make use of the limited communication resources, we then formulate an optimization problem to maximize the system utility for content distribution. To solve the complex optimization problem effectively, we first divide the road into small segments. Then, we propose a fuzzy-logic-based method to select the most proper content replica vehicle (CRV) for aiding content distribution and redefine the number of content request vehicles in each segment. Thereafter, the optimization problem is transformed into a nonlinear integer programming problem. Inspired by the artificial immune system, we propose an immune clone-based algorithm to solve it, which has a fast convergence to an optimal solution. Extensive simulations validate the effectiveness of our proposed EdgeVCD in terms of system utility, average utility, and convergence.

关键词： Content distribution dual-importance (DI) evaluation fuzzy logic immune clone intelligent algorithm vehicular edge computing (VEC) network

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An intelligent algorithm Based on Bacteria Foraging Optimization and Robust Fuzzy algorithm to Analyze Asthma Data

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INTERNATIONAL JOURNAL OF FUZZY SYSTEMS 2017年第4期19卷 1181-1189页

作者： Yang, Ming-Ren Lee, Zne-Jung Lee, Chou-Yuan Peng, Bin-Yu Huang, Hsiang Natl Taiwan Univ Sci & Technol Dept Elect Engn Taipei Taiwan Huafan Univ Dept Informat Management New Taipei Taiwan Lan Yang Inst Technol Dept Informat Management Yilan Taiwan Univ Kang Ning Dept Informat Management Tainan Taiwan Huafan Univ Dept Mechatron Engn Taipei Taiwan

Asthma has become the serious chronic and the most common disease of hospitalization in children. Recently, the number of children with asthma has increased year by year. Thereafter, the medical community pays much attention to the treatment of asthma. Because of noises or outlier, the resulting factors for asthma are complex. Traditional algorithms usually assume that asthma data are evenly distributed among various classes and might ignore minority classes. Therefore, an intelligent algorithm based on bacterial foraging optimization (BFO) and robust fuzzy algorithm (RFA) is applied to analyze asthma data in this paper. In the proposed algorithm, RFA with the property of robust can reduce the influence of noises or outlier. It can establish the fuzzy model and effectively analyze asthma data. For foraging theory, natural selection trends to eliminate animals with poor foraging strategies and to favor the propagation of genes for animals which have successful foraging strategies. BFO can model the mechanism of natural selection and find the best solution. Consequently, it can enhance the classification accuracy of asthma data. In this paper, asthma data were collected from Mackay Memorial Hospital in Taiwan to test the performance of the proposed algorithm. The performance of the proposed algorithm is supported by simulation results. From simulation results, the classification accuracy of the proposed algorithm outperforms other existing approaches and can help physicians to determine asthma.

关键词： intelligent algorithm Robust fuzzy algorithm Bacterial foraging optimization Asthma

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Anti-jamming technology of electronic communication based on improved intelligent algorithm

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JOURNAL OF intelligent & FUZZY SYSTEMS 2019年第5期37卷 5837-5847页

作者： Cheng, Weidong Beijing Informat Technol Coll Dept Traff Engn Beijing 100015 Peoples R China

intelligent interference communication technology is an important direction for the development of a new generation of anti jamming communication system through the recognition of complex electromagnetic interference environment and the use of learning and intelligent decision-making methods to achieve efficient and reliable information transmission. A channel prediction algorithm based on intelligent interference communication technology is proposed, and only a small-scale fading channel model is considered. Under the background of rapid development of information technology, the level of anti-interference of electronic communication is further improved, and the reliability of information transmission is effectively guaranteed. Under the background of fully expounding the physical layer security technology, the anti-interference scheme in large-scale multi-antenna system in electronic communication is designed. Based on the physical layer security communication model in the full-duplex network, a channel prediction scheme is innovatively proposed to reduce the impact of imperfect CSI. Through this measure to improve network security performance, the proposed anti-interference scheme was tested. The test results show that because Massive MIMO can direct the transmit beam and energy to the user direction, in the physical layer security scenario, for malicious eavesdroppers in the network, it cannot steal information and is difficult to interfere with electronic communication.

关键词： intelligent algorithm electronic communications anti-jamming technology

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Study on generation of abrasive protrusion height based on projection information-driven intelligent algorithm

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2022年第11-12期123卷 4309-4320页

作者： Li, Hongyang Fang, Congfu Huaqiao Univ Coll Mech Engn & Automat Xiamen 361021 Peoples R China

Abrasive protrusion height (APH) is the core parameter of abrasive tools, and it is also a principal parameter for modeling and simulation of the surface topography of abrasive tools. Because of the difficulty in obtaining the 3D feature information of abrasives and the limited measured data;this study proposes an APH model based on the spatial projection relationship. Combined with the gradient boosting decision tree (GBDT) intelligent algorithm, the APH characteristics of the abrasive tool are quickly generated by the data-fusion learning model. Through the corresponding experiments, we acquired the 2D image of the abrasive tool and extracted the area information of the abrasive projection area. The result shows that the fitting degree R-2 of the algorithm model reaches 0.911. Comparing the APH generated based on the algorithm model with the actual one, the average accuracy is about 94.69% and the mean absolute error of generated protrusion height MAE is 5.31 mu m, which validates the proposed model. The results of this study demonstrate that the data-driven approach can effectively establish the generation model of the protrusion height of abrasive grains, which not only enable the measurement of the protrusion height of abrasive but also provide a reference for accurate modeling of abrasive tools.

关键词： Abrasive tool Protrusion height Abrasive image Data-fusion intelligent algorithm

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An intelligent algorithm for the Protection of Smart Power Systems

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IEEE TRANSACTIONS ON SMART GRID 2013年第3期4卷 1541-1548页

作者： Xyngi, Ioanna Popov, Marjan Siemens AG D-91058 Erlangen Germany Delft Univ Technol Fac EEMCS NL-2628 CD Delft Netherlands

The paper proposes a new concept of protection philosophy for Dutch distribution grids with high penetration of renewable energy. Conventional protection concepts are normally based on protection schemes that consist of definite or inverse time overcurrent relays. In future power systems, these schemes can lead to high fault clearing times, unselective tripping and massive DG disconnections, which are not acceptable in a deregulated multi-owner energy market. This research work proposes an efficient intelligent communication-based protection algorithm that implements different multi-functional protection principles supported by blocking schemes. The real-time organization of both the hardware architecture and communication infrastructure of the protection algorithm is illustrated in detail. Special emphasis is given to the network reconfiguration scenario cases and detailed simulation results of such illustrative studied cases are provided. The new protection strategy guarantees protection selectivity and provides DG-unit availability during and after the fault. The intelligent algorithm is applied on existing Dutch distribution network and meaningful conclusions are derived.

关键词： Communication-based protection DG availability intelligent algorithm modeling selectivity

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An intelligent algorithm with feature selection and decision rules applied to anomaly intrusion detection

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APPLIED SOFT COMPUTING 2012年第10期12卷 3285-3290页

作者： Lin, Shih-Wei Ying, Kuo-Ching Lee, Chou-Yuan Lee, Zne-Jung Huafan Univ Dept Informat Management Shihding Dist 22301 New Taipei Coun Taiwan Chang Gung Univ Dept Informat Management Tao Yuan Taiwan Natl Taipei Univ Technol Dept Ind Engn & Management Taipei 10608 Taiwan

Intrusion detection system (IDS) is to monitor the attacks occurring in the computer or networks. Anomaly intrusion detection plays an important role in IDS to detect new attacks by detecting any deviation from the normal profile. In this paper, an intelligent algorithm with feature selection and decision rules applied to anomaly intrusion detection is proposed. The key idea is to take the advantage of support vector machine (SVM), decision tree (DT), and simulated annealing (SA). In the proposed algorithm, SVM and SA can find the best selected features to elevate the accuracy of anomaly intrusion detection. By analyzing the information from using KDD'99 dataset, DT and SA can obtain decision rules for new attacks and can improve accuracy of classification. In addition, the best parameter settings for the DT and SVM are automatically adjusted by SA. The proposed algorithm outperforms other existing approaches. Simulation results demonstrate that the proposed algorithm is successful in detecting anomaly intrusion detection. (C) 2012 Published by Elsevier B.V.

关键词： intelligent algorithm Anomaly detection Support vector machine Decision tree Simulated annealing

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IoT coverage based on intelligent algorithm

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CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS 2019年第6-Sup期22卷 14983-14989页

作者： Ge, Qianqian Zhejiang Business Technol Inst Ningbo 315012 Zhejiang Peoples R China

In order to improve the coverage of IoT, according to the characteristics of mass data, the data fusion in IoT coverage was hierarchically classified. At the same time, the LEACH routing algorithm and fuzzy algorithm were introduced in detail. The data was fused correctly. The routing algorithm was improved. The improved LEACH algorithm and fuzzy algorithm were simulated and the results were analyzed. The results showed that when the massive data was fused, the improved intelligent algorithm maximized the IoT coverage. Therefore, the improved algorithm can greatly reduce the node energy consumption. At the same time, it saves time.

关键词： intelligent algorithm Internet of things coverage Data fusion LEACH algorithm Fuzzy algorithm

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Feature extraction-based intelligent algorithm framework with neural network for solving conditional nonlinear optimal perturbation

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SOFT COMPUTING 2022年第14期26卷 6907-6924页

作者： Yuan, Shijin Zhang, Huazhen Liu, Yaxuan Mu, Bin Tongji Univ Sch Software Engn Shanghai 201804 Peoples R China

Conditional nonlinear optimal perturbation (CNOP) defines an optimization problem to study predictability and sensitivity of the oceanic and climatic events in the nonlinear system. One effective method to solve the corresponding problem is feature extraction-based intelligent algorithm (FEIA) framework. In the previous study, the mapper and the re-constructor of the framework are generally obtained by principal component analysis (PCA), but the solving performance still needs to further improve. Recently, neural network has attracted the attention of lots of researcher, and many structures of neural network can be used to construct the mapping-reconstruction structure of FEIA framework. However, the related studies applying neural network in FEIA framework are lacking. Compared with PCA, neural network might obtain a proper structure for FEIA framework with the well-directed training. Therefore, this paper suggests two ways applying neural network in FEIA framework, and the corresponding frameworks are tested to solve CNOP of double-gyre variation in Regional Ocean Modeling System (ROMS). The results show that FEIA framework with neural network can obtain the solutions with better objective function values, and the corresponding solutions have a larger probability leading to the related physical phenomenon.

关键词： Neural network intelligent algorithm Large-scale optimization Dimension reduction Conditional nonlinear optimal perturbation

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A complex contract negotiation model based on hybrid intelligent algorithm

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CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS 2019年第6-Sup期22卷 14317-14325页

作者： Li, Mei Song, Jiasheng Wang, Gaofei Chen, Peiyou Harbin Univ Sci & Technol Sch Management Harbin Heilongjiang Peoples R China Heilongjiang Univ Sci & Technol Sch Management Harbin Heilongjiang Peoples R China

intelligent negotiation plays an important role in e-commerce. In the research of multi-attribute negotiation, the non-linear relationship between attributes is usually neglected. Multi-attribute multilateral negotiation model with such complex relationship is more practical. In this paper, the building of a multilateral negotiation model of complex contracts with nonlinear dependencies between attributes by applying Multi-Agent System and hybrid intelligent algorithm is studied. And the approximate optimal solution of Nash equilibrium within a certain accuracy range is given. Finally, through simulation examples of multilateral negotiation with two attributes of price and quality, the correctness and validity of the method are verified. The research provides new ideas for intelligent negotiation research.

关键词： Complex contract Negotiation model intelligent algorithm MAS

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