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  • Open Access


    Agricultural Investment Project Decisions Based on an Interactive Preference Disaggregation Model Considering Inconsistency

    Xingli Wu1,{{sup}}#{{/sup}}, Huchang Liao1,{{sup}}#{{/sup}}, Shuxian Sun1, Zhengjun Wan2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3125-3146, 2024, DOI:10.32604/cmes.2023.047031

    Abstract Agricultural investment project selection is a complex multi-criteria decision-making problem, as agricultural projects are easily influenced by various risk factors, and the evaluation information provided by decision-makers usually involves uncertainty and inconsistency. Existing literature primarily employed direct preference elicitation methods to address such issues, necessitating a great cognitive effort on the part of decision-makers during evaluation, specifically, determining the weights of criteria. In this study, we propose an indirect preference elicitation method, known as a preference disaggregation method, to learn decision-maker preference models from decision examples. To enhance evaluation ease, decision-makers merely need to compare… More >

  • Open Access


    Evaluating the Derivative Value of Smart Grid Investment under Dual Carbon Target: A Hybrid Multi-Criteria Decision-Making Analysis

    Na Yu1, Changzheng Gao2, Xiuna Wang2, Dongwei Li2,*, Weiyang You2

    Energy Engineering, Vol.120, No.12, pp. 2879-2901, 2023, DOI:10.32604/ee.2023.029426

    Abstract With the goal of “carbon peaking and carbon neutralization”, it is an inevitable trend for investing smart grid to promote the large-scale grid connection of renewable energy. Smart grid investment has a significant driving effect (derivative value), and evaluating this value can help to more accurately grasp the external effects of smart grid investment and support the realization of industrial linkage value with power grid investment as the core. Therefore, by analyzing the characterization of the derivative value of smart grid driven by investment, this paper constructs the evaluation index system of the derivative value… More >

  • Open Access


    Study on Comprehensive Efficiency Evaluation of Rural Power Grid under Rural Revitalization Strategy Considering Regional Differences

    Huiru Zhao1, Manyu Yao1,*, Zhenqi Bai1, Yue Zhang2, Zhihua Ding3, Zhenda Hu4

    Energy Engineering, Vol.120, No.10, pp. 2211-2231, 2023, DOI:10.32604/ee.2023.029371

    Abstract As an essential infrastructure, the rural power grid is vital in promoting agricultural and rural carbon sequestration and improving rural energy electrification. It is necessary to carry out in-depth research on its comprehensive efficiency. Based on the requirements of “double carbon” and rural revitalization strategy for the rural Power Grid, this paper focuses on the modernization and low-carbon transformation of the rural Power Grid. It constructs an input-output index system for the investment efficiency of the rural Power Grid in China under the new situation. It uses the primary data of the rural Power Grid… More >

  • Open Access


    Multi-Criteria Decision-Making for Power Grid Construction Project Investment Ranking Based on the Prospect Theory Improved by Rewarding Good and Punishing Bad Linear Transformation

    Shun Ma1, Na Yu1, Xiuna Wang2, Shiyan Mei1, Mingrui Zhao2,*, Xiaoyu Han2

    Energy Engineering, Vol.120, No.10, pp. 2369-2392, 2023, DOI:10.32604/ee.2023.028727

    Abstract Using the improved prospect theory with the linear transformations of rewarding good and punishing bad (RGPBIT), a new investment ranking model for power grid construction projects (PGCPs) is proposed. Given the uncertainty of each index value under the market environment, fuzzy numbers are used to describe qualitative indicators and interval numbers are used to describe quantitative ones. Taking into account decision-maker’s subjective risk attitudes, a multi-criteria decision-making (MCDM) method based on improved prospect theory is proposed. First, the [−1, 1] RGPBIT operator is proposed to normalize the original data, to obtain the best and worst More >

  • Open Access


    Stock Market Prediction Using Generative Adversarial Networks (GANs): Hybrid Intelligent Model

    Fares Abdulhafidh Dael1,*, Ömer Çağrı Yavuz2, Uğur Yavuz1

    Computer Systems Science and Engineering, Vol.47, No.1, pp. 19-35, 2023, DOI:10.32604/csse.2023.037903

    Abstract The key indication of a nation’s economic development and strength is the stock market. Inflation and economic expansion affect the volatility of the stock market. Given the multitude of factors, predicting stock prices is intrinsically challenging. Predicting the movement of stock price indexes is a difficult component of predicting financial time series. Accurately predicting the price movement of stocks can result in financial advantages for investors. Due to the complexity of stock market data, it is extremely challenging to create accurate forecasting models. Using machine learning and other algorithms to anticipate stock prices is an More >

  • Open Access


    The Effect of Self-Investment on Hoarding Tendency of Chinese College Students: Role of Psychological Connections

    Xiangli Guan1, Yue Zhang2, Yang Li1, Yaqi Zhang1,*, Jingjing Wang1, Xuejiao Li1, Mary C. Jobe3, Md Zahir Ahmed4, Oli Ahmed5

    International Journal of Mental Health Promotion, Vol.25, No.6, pp. 755-766, 2023, DOI:10.32604/ijmhp.2023.027086

    Abstract Because of factors such as energy and time one invests in an object, the stronger the connection, value, and reluctance to lose said object individual will have. Hoarding behavior arises when individuals incorporate a strong attachment with themselves to an object. The purpose of this study is to examine the effect of self-investment on hoarding tendency and the roles of possession-self link and liking level in this connection. A hypothetical model of the relationship between self-investment, possession-self link, liking level, and hoarding tendency was tested. A convenience sampling method was used to survey 450 college… More >

  • Open Access


    The Influence of Body Investment on Depression in Chinese College Students: A Moderated Mediating Effect

    Jingjing Wang1, Xiangli Guan1,*, Sumei Yin1, Sha Shen2, Xuejiao Li1, Md Zahir Ahmed3, Mary C. Jobe4, Oli Ahmed5

    International Journal of Mental Health Promotion, Vol.24, No.1, pp. 39-50, 2022, DOI:10.32604/ijmhp.2022.019635

    Abstract An individual’s perception, attitude, feeling and behavior about their body are important factors for mental health (depression). This study aims to explore the impact of body investment on depression, and the role of self-efficacy and self-esteem in this connection. A hypothetical model about the relationship between body investment, selfefficacy, self-esteem and depression was tested. Using convenient sampling methods, a self-rated cross-sectional survey comprised of paper-based and online modes was conducted among 1,164 college students in Yunnan Province, China from July 2021 to August 2021. The data collection used the body investment scale, self-efficacy scale, self-esteem… More >

  • Open Access


    Sustainable Investment Forecasting of Power Grids Based on the Deep Restricted Boltzmann Machine Optimized by the Lion Algorithm

    Qian Wang1, Xiaolong Yang2,*, Di Pu3, Yingying Fan4

    CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.1, pp. 269-286, 2022, DOI:10.32604/cmes.2022.016437

    Abstract This paper proposes a new power grid investment prediction model based on the deep restricted Boltzmann machine (DRBM) optimized by the Lion algorithm (LA). Firstly, two factors including transmission and distribution price reform (TDPR) and 5G station construction were comprehensively incorporated into the consideration of influencing factors, and the fuzzy threshold method was used to screen out critical influencing factors. Then, the LA was used to optimize the parameters of the DRBM model to improve the model's prediction accuracy, and the model was trained with the selected influencing factors and investment. Finally, the LA-DRBM model… More >

  • Open Access


    Evaluation and Forecasting of Wind Energy Investment Risk along the Belt and Road Based on a Novel Hybrid Intelligent Model

    Liping Yan1,*, Wei-Chiang Hong2

    CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.3, pp. 1069-1102, 2021, DOI:10.32604/cmes.2021.016499

    Abstract The timely and effective investment risk assessment and forecasting are of great significance to ensure the investment safety and sustainable development of wind energy along the Belt and Road. In order to obtain the scientific and real-time forecasting result, this paper constructs a novel hybrid intelligent model based on improved cloud model combined with GRA-TOPSIS and MBA-WLSSVM. Firstly, the factors influencing investment risk of wind energy along the Belt and Road are identified from three dimensions: endogenous risk, exogenous risk and process risk. Through the fuzzy threshold method, the final input index system is selected.… More >

  • Open Access


    Investigain: A Productive Asset Management Web Application

    Rabbani Rasha1, Mohammad Monirujjaman Khan1,*, Mehedi Masud2, Mohammed A. AlZain3

    Computer Systems Science and Engineering, Vol.38, No.2, pp. 151-164, 2021, DOI:10.32604/csse.2021.015314

    Abstract The Investigain is a progressive web application to make mutual funds investments through a Systematic Investment Plan. The application utilizes the web’s modern capabilities, such as Asynchronous JavaScript and XML (AJAX), JavaScript, and Hypertext Marker Language (HTML5). The application also uses a powerful relational database management system, such as MySQL, to display asset management information. The application has two portals, one for investors and one for a particular asset manager or asset management company. Each investor has an account in the investor portal. The investor can view his/her profile, current balance, balance history, dividends, the More >

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