An efficient forecasting model based on an improved fuzzy time series and a modified group search optimizer

Lee, Chin-Ling; Kuo, Shu-Yu; Lin, Cheng‐Jian

doi:10.1007/s10489-016-0857-0

Cited by 7 publications

(2 citation statements)

References 22 publications

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“…As an important part of the financial service system supporting the real economy, the stock market will also become a part of the country's core competitiveness [2]. With the vigorous development of the national economy, strong policy support, and the gradual improvement of the public's awareness of financial management, more and more institutions and individuals are actively participating in stock market transactions [3,4]. e demand for related financial services has also followed, so stock price forecasting has become an issue that professional analysts and investors attach great importance to it [5].…”

Section: Introductionmentioning

confidence: 99%

Research on Market Stock Index Prediction Based on Network Security and Deep Learning

2021

Security and Communication Networks

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As one of the most popular financial management methods, stocks have attracted more and more investors to participate. The risks of stock investment are relatively high. How to reduce risks and increase profits has become the most concerned issue for investors. Traditional stock forecasting models use forecasting models based on stock time series analysis, but time series models cannot consider the influence of investor sentiment on stock market changes. In order to use investor sentiment information to make more accurate stock market forecasts, this paper establishes a stock index forecast and network security model based on time series and deep learning. Based on the time series model, it is proposed to use CNN to extract in-depth emotional information to replace the basic emotional features of the emotional extraction level. At the data source level, other information sources, such as basic features, are introduced to further improve the predictive performance of the model. The results show that the algorithm is feasible and effective and can better predict the changes in the market stock index. This also proves that multiple information sources can improve the accuracy of model prediction more effectively than a single information source.

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Section: Introductionmentioning

confidence: 99%

Research on Market Stock Index Prediction Based on Network Security and Deep Learning

2021

Security and Communication Networks

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“…(a) MGSO [62][63][64]. It is based on a finder-searcher model, possessing a high efficiency regarding high-dimension multimodal optimization issues, so it has a broad application prospect in Pareto multi-object dynamic optimization field.…”

Section: Distribution Sidementioning

confidence: 99%

Local Energy Management and Optimization: A Novel Energy Universal Service Bus System Based on Energy Internet Technologies

et al. 2018

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This paper develops a novel energy universal service bus system (EUSBS) based on emerging energy Internet (E-net) technologies. This EUSBS is a unified identification and plug-and-play interface platform to which high penetration distributed energy and equipment (DEE), including photovoltaic (PV), fans, electric vehicle charging stations (EVCSs), energy storage equipment (ESE), and commercial and residential users (CRUs), can access in a coordinated control and optimized utilization mode. First, the functions design, overall framework and topology architecture design of the EUSBS are expounded, among which the EUSBS is mainly composed of a hardware system and a software platform. Moreover, several future application scenarios are presented. Then, the hardware part of EUSBS is designed and developed, including the framework design of this hardware subsystem, and development of the hardware equipment for PV access, fans access, EVCS access, ESE access, and CRU access. The hardware subsystem consists of smart socket, and household/floor/building concentrators. Based on this, the prototypes development of EUSBS hardware equipment is completely demonstrated. Third, the software part of the EUSBS is developed as a cloud service platform for electricity use data analysis of DEE. This software subsystem contains the power quality & energy efficiency analysis module, optimization control module, information and service module, and data monitoring and electricity behavior analysis module. Based on this design, the software interfaces are developed. Finally, an application study on energy management and optimization of a smart commercial building is conducted to evaluate the functions and practicality of this EUSBS. The EUSBS developed in this paper is able to overcome difficulties in big data collection and utilization on sides of distribution network and electricity utilization, and eventually implement a deep information-energy fusion and a friendly supply-demand interaction between the grid and users. This contribution presents a detailed and systematic development scheme of the EUSBS, and moreover, the laboratory prototypes of the hardware and software subsystems have been developed based on E-net technologies. This paper can provide some thoughts and suggestions for the research of active distribution network and comprehensive energy management and optimization in power systems, as well as references and guidance for researchers to carry out research regarding energy management, optimization and coordinated control of the smart buildings.

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RETRACTED ARTICLE: Group search optimizer: a nature-inspired meta-heuristic optimization algorithm with its results, variants, and applications

Abualigah

2020

Neural Comput & Applic

160

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An efficient forecasting model based on an improved fuzzy time series and a modified group search optimizer

Cited by 7 publications

References 22 publications

Research on Market Stock Index Prediction Based on Network Security and Deep Learning

Research on Market Stock Index Prediction Based on Network Security and Deep Learning

Local Energy Management and Optimization: A Novel Energy Universal Service Bus System Based on Energy Internet Technologies

RETRACTED ARTICLE: Group search optimizer: a nature-inspired meta-heuristic optimization algorithm with its results, variants, and applications

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