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  • Open Access


    An Optimal Method for Supply Chain Logistics Management Based on Neural Network

    Abdallah Abdallah1, Mohammed Dauwed2, Ayman A. Aly3, Bassem F. Felemban3, Imran Khan4, Bong Jun Choi5,*

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 4311-4327, 2022, DOI:10.32604/cmc.2022.031514

    Abstract From raw material storage through final product distribution, a cold supply chain is a technique in which all activities are managed by temperature. The expansion in the number of imported meat and other comparable commodities, as well as exported seafood has boosted the performance of cold chain logistics service providers. On the basis of the standard basic-pursuit (BP) neural network, a rough BP particle swarm optimization (PSO) neural network model is constructed by combining rough set and particle swarm algorithms to aid cold chain food production enterprises in quickly picking the best cold chain logistics service providers. To reduce duplicate… More >

  • Open Access


    Deep Learning Enabled Financial Crisis Prediction Model for Small-Medium Sized Industries

    Kavitha Muthukumaran*, K. Hariharanath

    Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 521-536, 2023, DOI:10.32604/iasc.2023.025968

    Abstract Recently, data science techniques utilize artificial intelligence (AI) techniques who start and run small and medium-sized enterprises (SMEs) to take an influence and grow their businesses. For SMEs, owing to the inexistence of consistent data and other features, evaluating credit risks is difficult and costly. On the other hand, it becomes necessary to design efficient models for predicting business failures or financial crises of SMEs. Various data classification approaches for financial crisis prediction (FCP) have been presented for predicting the financial status of the organization by the use of past data. A major process involved in the design of FCP… More >

  • Open Access


    Research on the Application of Big Data Technology in the Integration of Enterprise Business and Finance

    Hanbo Liu*, Guang Sun

    Journal on Big Data, Vol.3, No.4, pp. 175-182, 2021, DOI:10.32604/jbd.2021.024074

    Abstract With the advent of the era of big data, traditional financial management has been unable to meet the needs of modern enterprise business. Enterprises hope that financial management has the function of improving the accuracy of corporate financial data, assisting corporate management to make decisions that are more in line with the actual development of the company, and optimizing corporate management systems, thereby comprehensively improving the overall level of the company and ensuring that the company can be in business with the assistance of financial integration, can better improve and develop themselves. Based on the investigation of enterprises and universities,… More >

  • Open Access


    Artificial Intelligence Based Optimal Functional Link Neural Network for Financial Data Science

    Anwer Mustafa Hilal1, Hadeel Alsolai2, Fahd N. Al-Wesabi3, Mohammed Abdullah Al-Hagery4, Manar Ahmed Hamza1,*, Mesfer Al Duhayyim5

    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 6289-6304, 2022, DOI:10.32604/cmc.2022.021522

    Abstract In present digital era, data science techniques exploit artificial intelligence (AI) techniques who start and run small and medium-sized enterprises (SMEs) to have an impact and develop their businesses. Data science integrates the conventions of econometrics with the technological elements of data science. It make use of machine learning (ML), predictive and prescriptive analytics to effectively understand financial data and solve related problems. Smart technologies for SMEs enable allows the firm to get smarter with their processes and offers efficient operations. At the same time, it is needed to develop an effective tool which can assist small to medium sized… More >

  • Open Access


    Low-Carbon Efficiency Model Evaluation of China’s Iron and Steel Enterprises Based on Data and Empirical Evidence

    Xuesong Xu, Hongyan Shao, Shengjie Yang*, Rongyuan Chen

    Intelligent Automation & Soft Computing, Vol.26, No.5, pp. 1063-1072, 2020, DOI:10.32604/iasc.2020.010137

    Abstract The aim of this study is to consider the economic, resource, energy and environmental factors in a low-carbon economic efficiency evaluation system and to analyze the factors affecting iron and steel enterprises. A combined data envelopment analysis and Malmquist index model have been used in this paper. We empirically investigate the low-carbon efficiency of the Chinese steel industry using observations of 17 listed enterprises from 2009 to 2013. The results show that the economic efficiency of China’s iron & steel enterprises is generally low. The Malmquist productivity index also shows a decreasing trend. Based on our findings, some policies are… More >

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