Xingli Wu^{1,{{sup}}#{{/sup}}}, Huchang Liao^{1,{{sup}}#{{/sup}}}, Shuxian Sun¹, Zhengjun Wan^2,*

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 pairs of alternatives with which… More >

Na Yu¹, Changzheng Gao², Xiuna Wang², Dongwei Li^2,*, 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 of smart grid investment including… More >

Huiru Zhao¹, Manyu Yao^1,*, 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 of 30 prefecture-level cities in… More >

Shun Ma¹, Na Yu¹, Xiuna Wang², Shiyan Mei¹, Mingrui Zhao^2,*, 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 schemes of PGCPs. Furthermore, the… More >

Fares Abdulhafidh Dael^1,*, 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 interesting area. The purpose of… More >

Xiangli Guan¹, Yue Zhang², Yang Li¹, Yaqi Zhang^1,*, 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 students in Yunnan Province on… More >

Jingjing Wang¹, Xiangli Guan^1,*, 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 scale and depression scale. The… More >

Qian Wang¹, Xiaolong Yang^2,*, 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 was used to predict the… More >

Liping Yan^1,*, 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. Secondly, the risk evaluation method… More >

Rabbani Rasha¹, Mohammad Monirujjaman Khan^1,*, 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 units of mutual funds bought,… More >