Real estate has been a dominant industry in many countries. One problem for real estate companies is determining the most valuable area before starting a new project. Previous studies on this issue mainly focused on m...Real estate has been a dominant industry in many countries. One problem for real estate companies is determining the most valuable area before starting a new project. Previous studies on this issue mainly focused on market needs and economic prospects, ignoring the impact of natural disasters. We observe that natural disasters are important for real estate area selection because they will introduce considerable losses to real estate enterprises. Following this observation, we first develop a self-defined new indicator named Average Loss Ratio to predict the losses caused by natural disasters in an area. Then, we adopt the existing ARIMA model to predict the Average Loss Ratio of an area. After that, we propose to integrate the TOPSIS model and the Grey Prediction Model to rank the recommendation levels for candidate areas, thereby assisting real estate companies in their decision-making process. We conduct experiments on real datasets to validate our proposal, and the results suggest the effectiveness of the proposed method.展开更多
According to the size of the projector function to evaluate the merits of the program, Projection Pursuit method is applied to real estate investment decision-making by using the real coding based on Accelerating Gene...According to the size of the projector function to evaluate the merits of the program, Projection Pursuit method is applied to real estate investment decision-making by using the real coding based on Accelerating Genetic Algorithm (RAGA) to optimize the Projection Pursuit Classification (PPC) process and a wide range of indicators value was projected linearly. The results are reasonable and verified with an example. At the same time, the subjective of the target weight can be avoided. It provides decision-makers with comprehensive information on all the indicators of new ideas and new展开更多
Background:Individual decision-making largely influences the effectiveness of decisions and benefits of investments.Methods:In this article,a consensus model for group decision-making(GDM),based on the analytic hierar...Background:Individual decision-making largely influences the effectiveness of decisions and benefits of investments.Methods:In this article,a consensus model for group decision-making(GDM),based on the analytic hierarchy process(AHP),is developed to gather group ideas and analyze the real estate investment environment under multi-criteria problems.Twelve evaluation procedures of the developed model,which increase the convergence of the opinions of multiple experts,are proposed.Results:An empirical case about the real estate investment environment is applied to certify the feasibility of this developed model.Conclusions:the evaluation procedures have been fully observed with several rounds of discussions,and have manifested the experiences of experts.Besides,the evaluation results are in accordance with real-world situations,which demonstrates that our developed model is a feasible analysis tool for real estate investors to obtain better profits and lower risk.展开更多
The objective of this research will be to calculate the feasibility of investing in a solar energy generation project through the development of a methodology that allows the capture of environmental uncertainties by ...The objective of this research will be to calculate the feasibility of investing in a solar energy generation project through the development of a methodology that allows the capture of environmental uncertainties by improving decision making. The article presents a comparative study of the feasibility analysis of investment in a solar mini solar energy for a Shopping, considering a regime of certainty and uncertainty. The assumed stochastic variables were energy tariff and price of solar panels. The trajectories were simulated with the binomial approach that combined resulted in a quadratic diagram. The applied methodology presented the best recommendation and the option to wait was the most valuable. The exchange of the energy obtained from LIGHT by own generation of energy with solar photovoltaic source will be viable for the manager since it observes the behavior of the variables over time and follows the rules of optimal decision.展开更多
文摘Real estate has been a dominant industry in many countries. One problem for real estate companies is determining the most valuable area before starting a new project. Previous studies on this issue mainly focused on market needs and economic prospects, ignoring the impact of natural disasters. We observe that natural disasters are important for real estate area selection because they will introduce considerable losses to real estate enterprises. Following this observation, we first develop a self-defined new indicator named Average Loss Ratio to predict the losses caused by natural disasters in an area. Then, we adopt the existing ARIMA model to predict the Average Loss Ratio of an area. After that, we propose to integrate the TOPSIS model and the Grey Prediction Model to rank the recommendation levels for candidate areas, thereby assisting real estate companies in their decision-making process. We conduct experiments on real datasets to validate our proposal, and the results suggest the effectiveness of the proposed method.
文摘According to the size of the projector function to evaluate the merits of the program, Projection Pursuit method is applied to real estate investment decision-making by using the real coding based on Accelerating Genetic Algorithm (RAGA) to optimize the Projection Pursuit Classification (PPC) process and a wide range of indicators value was projected linearly. The results are reasonable and verified with an example. At the same time, the subjective of the target weight can be avoided. It provides decision-makers with comprehensive information on all the indicators of new ideas and new
基金2016 Soft Science Research Project of Jiangxi Province(#20161BBA10081)Scientific research start-up project(#2003414092)+2 种基金Science and technology project of Department of Education of Jiangxi Province(#GJJ150512)Major project of Education Science"Thirteen Five"Planning Project of Jiangxi Province(#16ZD019)Grants from the National Natural Science Foundation of China(#71433001).
文摘Background:Individual decision-making largely influences the effectiveness of decisions and benefits of investments.Methods:In this article,a consensus model for group decision-making(GDM),based on the analytic hierarchy process(AHP),is developed to gather group ideas and analyze the real estate investment environment under multi-criteria problems.Twelve evaluation procedures of the developed model,which increase the convergence of the opinions of multiple experts,are proposed.Results:An empirical case about the real estate investment environment is applied to certify the feasibility of this developed model.Conclusions:the evaluation procedures have been fully observed with several rounds of discussions,and have manifested the experiences of experts.Besides,the evaluation results are in accordance with real-world situations,which demonstrates that our developed model is a feasible analysis tool for real estate investors to obtain better profits and lower risk.
文摘The objective of this research will be to calculate the feasibility of investing in a solar energy generation project through the development of a methodology that allows the capture of environmental uncertainties by improving decision making. The article presents a comparative study of the feasibility analysis of investment in a solar mini solar energy for a Shopping, considering a regime of certainty and uncertainty. The assumed stochastic variables were energy tariff and price of solar panels. The trajectories were simulated with the binomial approach that combined resulted in a quadratic diagram. The applied methodology presented the best recommendation and the option to wait was the most valuable. The exchange of the energy obtained from LIGHT by own generation of energy with solar photovoltaic source will be viable for the manager since it observes the behavior of the variables over time and follows the rules of optimal decision.
