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Article
Publication date: 14 May 2018

Lingling Li, Yanfang Yang, Ming-Lang Tseng, Ching-Hsin Wang and Ming K. Lim

The purpose of this paper is to deal with the economic requirements of power system loading dispatch and reduce the fuel cost of generation units. In order to optimize the…

251

Abstract

Purpose

The purpose of this paper is to deal with the economic requirements of power system loading dispatch and reduce the fuel cost of generation units. In order to optimize the scheduling of power load, an improved chicken swarm optimization (ICSO) is proposed to be adopted, for solving economic load dispatch (ELD) problem.

Design/methodology/approach

The ICSO increased the self-foraging factor to the chicks whose activities were the highest. And the evolutionary operations of chicks capturing the rooster food were increased. Therefore, these helped the ICSO to jump out of the local extreme traps and obtain the global optimal solution. In this study, the generation capacity of the generation unit is regarded as a variable, and the fuel cost is regarded as the objective function. The particle swarm optimization (PSO), chicken swarm optimization (CSO), and ICSO were used to optimize the fuel cost of three different test systems.

Findings

The result showed that the convergence speed, global search ability, and total fuel cost of the ICSO were better than those of PSO and CSO under different test systems. The non-linearity of the input and output of the generating unit satisfied the equality constraints; the average ratio of the optimal solution obtained by PSO, CSO, and ICSO was 1:0.999994:0.999988. The result also presented the equality and inequality constraints; the average ratio of the optimal solution was 1:0.997200:0.996033. The third test system took the non-linearity of the input and output of the generating unit that satisfied both equality and inequality constraints; the average ratio was 1:0.995968:0.993564.

Practical implications

This study realizes the whole fuel cost minimization in which various types of intelligent algorithms have been applied to the field of load economic scheduling. With the continuous evolution of intelligent algorithms, they save a lot of fuel cost for the ELD problem.

Originality/value

The ICSO is applied to solve the ELD problem. The quality of the optimal solution and the convergence speed of ICSO are better than that of CSO and PSO. Compared with PSO and CSO, ICSO can dispatch the generator more reasonably, thus saving the fuel cost. This will help the power sector to achieve greater economic benefits. Hence, the ICSO has good performance and significant effectiveness in solving the ELD problem.

Details

Industrial Management & Data Systems, vol. 118 no. 4
Type: Research Article
ISSN: 0263-5577

Keywords

Available. Open Access. Open Access
Article
Publication date: 14 May 2019

Haijian Li, Zhufei Huang, Lingqiao Qin, Shuo Zheng and Yanfang Yang

The purpose of this study is to effectively optimize vehicle lane-changing behavior and alleviate traffic congestion in ramp area through the study of vehicle lane-changing…

1215

Abstract

Purpose

The purpose of this study is to effectively optimize vehicle lane-changing behavior and alleviate traffic congestion in ramp area through the study of vehicle lane-changing behaviors in upstream segment of ramp areas.

Design/methodology/approach

In the upstream segment of ramp areas under a connected vehicle environment, different strategies of vehicle group lane-changing behaviors are modeled to obtain the best group lane-changing strategy. The traffic capacity of roads can be improved by controlling group lane-changing behavior and continuously optimizing lane-changing strategy through connected vehicle technologies. This paper constructs vehicle group lane-changing strategies in upstream segment of ramp areas under a connected vehicle environment. The proposed strategies are simulated by VISSIM.

Findings

The results show that different lane-changing strategies are modeled through vehicle group in the upstream segment of ramp areas, which can greatly reduce the delay of ramp areas.

Originality/value

The simulation results verify the validity and rationality of the corresponding vehicle group lane-changing behavior model strategies, effectively standardize the driver's lane-changing behavior, and improve road safety and capacity.

Details

Smart and Resilient Transportation, vol. 1 no. 1
Type: Research Article
ISSN: 2632-0487

Keywords

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Book part
Publication date: 7 October 2010

Feng Yang, Yanfang Yuan, Liang Liang and Zhimin Huang

The study on output allocative efficiency considering the emission trading is meaningful to allocate emission quota in order to promote production efficiency of industry. This…

Abstract

The study on output allocative efficiency considering the emission trading is meaningful to allocate emission quota in order to promote production efficiency of industry. This chapter studies the output allocation problem with constraints to profit and pollution goals, and proposes three types of output allocative efficiency measures, including the comprehensive output allocative efficiency, the profit-oriented output allocative efficiency based on pollution constraint, and the pollution-oriented output allocative efficiency based on profit constraint, which aim to maximize the total profit and (or) minimize the total pollution. The proposed measures are used to evaluate the output allocative efficiencies of 32 paper mills along the Huai River in China, and different parameters are tested with sensitivity analysis to examine the changes of optimal output combination. This chapter helps the enterprise to optimize the decision of production and helps the government to formulate a reasonable plan of pollution control and treatment.

Details

Applications in Multicriteria Decision Making, Data Envelopment Analysis, and Finance
Type: Book
ISBN: 978-0-85724-470-3

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Article
Publication date: 4 November 2024

Jiaqi Fang, Kun Ma, Yanfang Qiu, Ke Ji, Zhenxiang Chen and Bo Yang

The discrepancy between the content of an article and its title is a key characteristic of fake news. Current methods for detecting fake news often ignore the significant…

19

Abstract

Purpose

The discrepancy between the content of an article and its title is a key characteristic of fake news. Current methods for detecting fake news often ignore the significant difference in length between the content and its title. In addition, relying solely on textual discrepancies between the title and content to distinguish between real and fake news has proven ineffective. The purpose of this paper is to develop a new approach called semantic enhancement network with content–title discrepancy (SEN–CTD), which enhances the accuracy of fake news detection.

Design/methodology/approach

The SEN–CTD framework is composed of two primary modules: the SEN and the content–title comparison network (CTCN). The SEN is designed to enrich the representation of news titles by integrating external information and position information to capture the context. Meanwhile, the CTCN focuses on assessing the consistency between the content of news articles and their corresponding titles examining both emotional tones and semantic attributes.

Findings

The SEN–CTD model performs well on the GossipCop, PolitiFact and RealNews data sets, achieving accuracies of 80.28%, 86.88% and 84.96%, respectively. These results highlight its effectiveness in accurately detecting fake news across different types of content.

Originality/value

The SEN is specifically designed to improve the representation of extremely short texts, enhancing the depth and accuracy of analyses for brief content. The CTCN is tailored to examine the consistency between news titles and their corresponding content, ensuring a thorough comparative evaluation of both emotional and semantic discrepancies.

Details

International Journal of Web Information Systems, vol. 20 no. 6
Type: Research Article
ISSN: 1744-0084

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Article
Publication date: 11 July 2016

Madhuri Siddula, Fei Dai, Yanfang Ye and Jianping Fan

Roofing is one of the most dangerous jobs in the construction industry. Due to factors such as lack of planning, training and use of precaution, roofing contractors and workers…

748

Abstract

Purpose

Roofing is one of the most dangerous jobs in the construction industry. Due to factors such as lack of planning, training and use of precaution, roofing contractors and workers continuously violate the fall protection standards enforced by the US Occupational Safety and Health Administration. A preferable way to alleviate this situation is automating the process of non-compliance checking of safety standards through measurements conducted in site daily accumulated videos and photos. As a key component, the purpose of this paper is to devise a method to detect roofs in site images that is indispensable for such automation process.

Design/methodology/approach

This method represents roof objects through image segmentation and visual feature extraction. The visual features include colour, texture, compactness, contrast and the presence of roof corner. A classification algorithm is selected to use the derived representation for statistical learning and detection.

Findings

The experiments led to detection accuracy of 97.50 per cent, with over 15 per cent improvement in comparison to conventional classifiers, signifying the effectiveness of the proposed method.

Research limitations/implications

This study did not test on images of roofs in the following conditions: roofs initially built without apparent appearance (e.g. structural roof framing completed and undergoing the sheathing process) and flat, barrel and dome roofs. From a standpoint of construction safety, while the present work is vital, coupling with semantic representation and analysis is still needed to allow for risk analysis of fall violations on roof sites.

Originality/value

This study is the first to address roof detection in site images. Its findings provide a basis to enable semantic representation of roof site objects of interests (e.g. co-existence and correlation among roof site, roofer, guardrail and personal fall arrest system) that is needed to automate the non-compliance checking of safety standards on roof sites.

Details

Construction Innovation, vol. 16 no. 3
Type: Research Article
ISSN: 1471-4175

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Article
Publication date: 24 January 2025

Yanfang Qiu, Kun Ma, Weijuan Zhang, Run Pan and Zhenxiang Chen

Fake news refers to intentionally fabricated or misleading information designed to deceive the public and manipulate opinions for personal, political or financial gain. Most…

5

Abstract

Purpose

Fake news refers to intentionally fabricated or misleading information designed to deceive the public and manipulate opinions for personal, political or financial gain. Most existing detection methods primarily focus on capturing language features from news content. However, these methods neglect the varying importance of different news entities. Additionally, these methods tend to overlook the auxiliary role of external knowledge, resulting in an incomplete understanding of the entity. To address these issues, this paper aims to propose a Dual-layer Semantic Information Extraction Network with External Knowledge (DSEN-EK) for fake news detection.

Design/methodology/approach

This approach is proposed to comprise three parts: Dual-layer Semantic Information Extraction Network, Entity Integration Network with External Knowledge and Classifier. Specifically, Dual-layer Semantic Information Extraction Network is designed to enhance relationships between entities and the influence of important entity representations. The Entity Integration Network with External Knowledge is proposed to extract entity descriptions from external knowledge bases.

Findings

The DSEN-EK model performs well on the Liar, Constraint, Twitter15 and Twitter16 data sets, achieving accuracy of 98.02%, 94.61%, 90.09% and 93.65%, respectively. These results highlight its effectiveness in detecting fake news across different types of content.

Originality/value

The Dual-layer Semantic Information Extraction Network is proposed to capture the relationships between entities and enhance the continuous semantic information of the news. The Entity Integration Network with External Knowledge is designed to enrich entity descriptions, leading to a more comprehensive capture of semantic details.

Details

International Journal of Web Information Systems, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1744-0084

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Article
Publication date: 8 March 2022

Guijie Zhang, Fangfang Wei, Chunyan Guo and Yanfang Wang

This paper aims to present a longitudinal and visualising study using bibliometric approaches to depict the emerging trends and research hotspots within the mobile information…

500

Abstract

Purpose

This paper aims to present a longitudinal and visualising study using bibliometric approaches to depict the emerging trends and research hotspots within the mobile information system domain.

Design/methodology/approach

Publications included in the Web of Science (WoS) database for 2001–2021 are reviewed and analysed on various aspects through coauthorship, cocitation and co-occurrence analysis. The analyses are conducted using VOSViewer, a scientific visualisation software program.

Findings

Academic publications related to mobile information systems fluctuated at a low level during the initial part of the 21st century and have grown rapidly in number in the past decade. The USA and China are the leading contributors to these publications and hold dominant positions in the obtained collaboration network. Computer science, engineering and telecommunications are the top three research areas in which mainstream mobile information system research occurs. Moreover, medical informatics and health-care science services have gradually become new research hotspots.

Originality/value

This study provides a systematic and holistic account of the developmental landscape of the mobile information system domain. This study provides a good basis for analysing the evolution of research in mobile information systems and may serve as a potential foundation for future research.

Details

The Electronic Library , vol. 40 no. 3
Type: Research Article
ISSN: 0264-0473

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Article
Publication date: 14 December 2022

Lu An, Yan Shen, Yanfang Tao, Gang Li and Chuanming Yu

This study aims to profile the government microbloggers and evaluate their roles. The results can help improve the governments' response capability to public emergencies.

251

Abstract

Purpose

This study aims to profile the government microbloggers and evaluate their roles. The results can help improve the governments' response capability to public emergencies.

Design/methodology/approach

This study proposes the user profiling and role evaluation model of government microbloggers in the context of public emergencies. The indicators are designed from the four dimensions of time, content, scale and influence, and the feature labels are identified. Three different public emergencies were investigated, including the West Africa Ebola outbreak, the Middle East respiratory syndrome outbreak and the Shandong vaccine case in China.

Findings

The results found that most government microbloggers were follower responders, short-term participants, originators, occasional participants and low influencers. The role distribution of government microbloggers was highly concentrated. However, in terms of individual profiles, the role of a government microblogger varied with events.

Social implications

The findings can provide a reference for the performance assessment of the government microbloggers in the context of public emergencies and help them improve their ability to communicate with the public and respond to public emergencies.

Originality/value

By analyzing the performance of government microbloggers from the four dimensions of time, content, scale and influence, this paper fills the gap in existing literature on designing the user profiling and role evaluation model of government microbloggers in the context of public emergencies.

Details

Online Information Review, vol. 47 no. 6
Type: Research Article
ISSN: 1468-4527

Keywords

Available. Content available
Book part
Publication date: 7 October 2010

Abstract

Details

Applications in Multicriteria Decision Making, Data Envelopment Analysis, and Finance
Type: Book
ISBN: 978-0-85724-470-3

Available. Open Access. Open Access
Article
Publication date: 15 February 2021

Qi Sun, Fang Sun, Cai Liang, Chao Yu and Yamin Zhang

Beijing rail transit can actively control the density of rail transit passenger flow, ensure travel facilities and provide a safe and comfortable riding atmosphere for rail…

845

Abstract

Purpose

Beijing rail transit can actively control the density of rail transit passenger flow, ensure travel facilities and provide a safe and comfortable riding atmosphere for rail transit passengers during the epidemic. The purpose of this paper is to efficiently monitor the flow of rail passengers, the first method is to regulate the flow of passengers by means of a coordinated connection between the stations of the railway line; the second method is to objectively distribute the inbound traffic quotas between stations to achieve the aim of accurate and reasonable control according to the actual number of people entering the station.

Design/methodology/approach

This paper analyzes the rules of rail transit passenger flow and updates the passenger flow prediction model in time according to the characteristics of passenger flow during the epidemic to solve the above-mentioned problems. Big data system analysis restores and refines the time and space distribution of the finely expected passenger flow and the train service plan of each route. Get information on the passenger travel chain from arriving, boarding, transferring, getting off and leaving, as well as the full load rate of each train.

Findings

A series of digital flow control models, based on the time and space composition of passengers on trains with congested sections, has been designed and developed to scientifically calculate the number of passengers entering the station and provide an operational basis for operating companies to accurately control flow.

Originality/value

This study can analyze the section where the highest full load occurs, the composition of passengers in this section and when and where passengers board the train, based on the measured train full load rate data. Then, this paper combines the full load rate control index to perform reverse deduction to calculate the inbound volume time-sharing indicators of each station and redistribute the time-sharing indicators for each station according to the actual situation of the inbound volume of each line during the epidemic. Finally, form the specified full load rate index digital time-sharing passenger flow control scheme.

Details

Smart and Resilient Transportation, vol. 3 no. 1
Type: Research Article
ISSN: 2632-0487

Keywords

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