Intelligent physical systems for strategic planning and management of enterprise information

Ye, Changyou; Song, Xiaowei; Vivekananda, G. N.; Savitha, V.

doi:10.1007/s12083-020-00966-7

Cited by 4 publications

(1 citation statement)

References 25 publications

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“…In order to ensure the data interaction between the four layers of the system, the server architecture of the system was built with the distributed cluster server architecture [13]. The distributed master-slave server architecture can transfer the fault point to the backup server.…”

Section: System Soa Architecture Designmentioning

confidence: 99%

Development and Application of Rural Tourism Information Service System Based on SOA Technology Framework

Du²

2023

SPEE

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Due to the development of the times and the rapid pace of life in the modern society, the living standards has become higher and higher, and various types of self-driving travel have begun to increase. However, at present, most rural areas do not have good infrastructures, tourist introduction platforms and tour guide services for tourism, and there is no effective guidance service for the rural complex traffic environment, so these problems restrict the development of rural tourism. In view of these problems, in this paper, the rural tourism information service system based on SOA technology framework was designed and developed to provide tourists with convenient services and to attract more tourists.

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Section: System Soa Architecture Designmentioning

confidence: 99%

Development and Application of Rural Tourism Information Service System Based on SOA Technology Framework

Du²

2023

SPEE

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A Deep Learning-Based Knowledge Graph Framework for Intelligent Management Scheduling Decision of Enterprises

Ma,

Fan

2023

J CIRCUIT SYST COMP

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Due to the huge magnitude expansion of data volume, the application of cloud computing and the Internet of Things is growing year by year. However, more and more industrial production requires real-time and efficient handling of resource scheduling. Therefore, this paper develops a deep learning-based knowledge graph framework for resource scheduling decision of enterprise. Single-objective and multi-objective problems for computing resources are studied, and the network nodes of computing resources are set with the help of network topology theory. For the single-objective problem, the mathematical model is constructed with the optimization objective of minimizing the time delay. For the multi-objective problem, the mathematical model is constructed with the optimization objectives of minimizing both time delay and energy consumption. Combining the historical scheduling scheme with the introduction of a genetic algorithm, an initial optimization method is proposed for the scheduling problem of mixed flow shop, and the optimization problem is solved to minimize the maximum completion time. The simulation experiments are conducted to evaluate the proposed method, and the obtained results show that the proposal can well realize intelligent management scheduling decision for enterprises.

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Development of big data assisted effective enterprise resource planning framework for smart human resource management

Zhao

2024

PLoS ONE

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The planning of human resources and the management of enterprises consider the organization’s size, the amount of effort put into operations, and the level of productivity. Inefficient allocation of resources in organizations due to skill-task misalignment lowers production and operational efficiency. This study addresses organizations’ poor resource allocation and use, which reduces productivity and the efficiency of operations, and inefficiency may adversely impact company production and finances. This research aims to develop and assess a Placement-Assisted Resource Management Scheme (PRMS) to improve resource allocation and usage and businesses’ operational efficiency and productivity. PRMS uses expertise, business requirements, and processes that are driven by data to match resources with activities that align with their capabilities and require them to perform promptly. The proposed system PRMS outperforms existing approaches on various performance metrics at two distinct levels of operations and operating levels, with a success rate of 0.9328% and 0.9302%, minimal swapping ratios of 12.052% and 11.658%, smaller resource mitigation ratios of 4.098% and 4.815%, mean decision times of 5.414s and 4.976s, and data analysis counts of 6387 and 6335 Success and data analysis increase by 9.98% and 8.2%, respectively, with the proposed strategy. This technique cuts the switching ratio, resource mitigation, and decision time by 6.52%, 13.84%, and 8.49%. The study concluded that PRMS is a solid, productivity-focused corporate improvement method that optimizes the allocation of resources and meets business needs.

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Intelligent physical systems for strategic planning and management of enterprise information

Cited by 4 publications

References 25 publications

Development and Application of Rural Tourism Information Service System Based on SOA Technology Framework

Development and Application of Rural Tourism Information Service System Based on SOA Technology Framework

A Deep Learning-Based Knowledge Graph Framework for Intelligent Management Scheduling Decision of Enterprises

Development of big data assisted effective enterprise resource planning framework for smart human resource management

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