Bio: Yihua Mao is an academic researcher from Zhejiang University. The author has contributed to research in topics: Risk assessment & Carbon neutrality. The author has an hindex of 1, co-authored 1 publications receiving 32 citations.
TL;DR: F fuzzy mathematics is used to assess the levels of income risk and cost risk in the real estate investment, and then adjust the relevant parameters of fuzzy real option based on the above risk assessment of real estate project, which will improve the rationality and validity of the engineering potential value evaluation.
TL;DR: In this paper , a multi-objective optimization operation model of microgrid access to 5G base station is built, where the objective is to minimize the operating cost and carbon emission.
Abstract: Abstract: a large number of 5G base station are connected, which provides a new possibility for the future low-carbon development of power systems. By encouraging 5G base station to participate in demand response and incorporating it into the Microgrid, it can reduce the power consumption cost of 5G base stations and promote the efficient utilization of renewable energy. Based on the microgrid operation structure, 5G base station and multi-objective problem algorithm, a multi-objective optimization operation model of microgrid access to 5G base station is built. Considering the physical constraints of Microgrid, the objective is to minimize the operating cost and carbon emission. Through the joint dispatching of distributed clean energy generation, micro gas turbine, energy storage system and 5G base station in Microgrid, the comprehensive optimization of system economy and low-carbon benefits can be achieved. In this paper, a microgrid in Beijing is taken as the research object, and the Whale Optimization Algorithm algorithm is used to solve the multiobjective problem. The analysis results show that 5G base station can flexibly respond to microgrid scheduling, which helps microgrid to improve the consumption and utilization efficiency of renewable energy, thus bringing higher economic benefits and low-carbon benefits, and helping China to achieve the goal of carbon peak shaving and carbon neutrality at an early date.
TL;DR: Fuzzy and hybrid methods have been increasingly used in construction risk management research and the Credal network – an extended form of Bayesian network- is found to have potential for risk assessment under uncertainty.
TL;DR: In this article, the authors provide an overview of the current literature on real options, thereby fulfilling a gap in current academic literature, and provide an extensive overview of their application to the infrastructure sector.
Abstract: Infrastructure networks are essential to support the world’s economic development. Governments around the world, in both developed and developing economies, have dedicated significant shares of the public budget to infrastructure development and refurbishment. Nevertheless, there has been an increasing concern about the selection of economically more interesting projects. The large sunk investments, as well as the uncertainty surrounding these projects, require new and more sophisticated investment analysis techniques. Simultaneously, there has been a recent trend towards increasing the flexibility in these projects to allow a more progressive adaptation to changing market conditions, thus decreasing the overall risk affecting these investments. The flexibility is introduced through real options that include the possibility of change that one develops in the planning and design stage, allowing the infrastructure (and service) to cope with future uncertainty. This paper intends to provide an overview of the current literature on real options, thereby fulfilling a gap in current academic literature. It addresses the main types of options and valuation mechanisms and provides an extensive overview of their application to the infrastructure sector.
TL;DR: In this article, an economic-probabilistic model for risk analysis in technological innovation (TI) projects is presented, which integrates risk and economic analysis by quantifying both value and probability of occurrence of cash flow deviations.
TL;DR: In this paper, a conceptual model, through fuzzy cognitive mapping, is presented to identify and understand the cause-and-effect relationships between the factors that represent an obstacle to real estate investments for residential rental purposes.
Abstract: The recent economic crisis led to significant changes in the real estate market; one of which was a shift toward home rental (rather than buying). Real estate investors have an important role in the growth of the rental market. However, there are often hindrances to investing for residential rental purposes. In order to overcome these barriers, they first need to be identified and understood. With this in mind, the main focus of this investigation was the creation of a conceptual model, through fuzzy cognitive mapping, to identify and understand the cause-and-effect relationships between the factors that represent an obstacle to real estate investments for residential rental purposes. The results show that cognitive maps can be of great use for the structuring of complex decision problems, minimizing the number of factors left out of the decision making process. In particular, the tenant risk behavior, property location and associated costs (for the owner) were identified as the main obstacles to real estate investment rental propose. The practical implications of the model, as well as the advantages and limitations of the process followed, are also discussed.
TL;DR: Interval type-2 fuzzy capital budgeting techniques are developed by using both triangular and trapezoidal interval type- 2 fuzzy sets and the results show that the techniques produce consistent outputs, which means that the developed techniques can be used interchangeably.
Abstract: Discounted cash flows methods are very pop- ular in justifying investments. Uncertainty in investment parameters always exists and is inevitable. The fuzzy set theory is capable to capture this uncertainty through the membership functions of these parameters. However, or- dinary fuzzy sets are criticized for having one single membership value for each certain parameter value. To remove this criticism, type-2 fuzzy sets were proposed. In this paper, we developed interval type-2 fuzzy capital budgeting techniques by using both triangular and trape- zoidal interval type-2 fuzzy sets. The developed techniques are interval type-2 fuzzy net present value analysis, interval type-2 fuzzy future value analysis, and interval type-2 fuzzy equivalent uniform annual value analysis. These techniques are applied to a part of a real life investment project. The results show that the techniques produce consistent outputs, which means that the developed tech- niques can be used interchangeably.