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optimal decision-making model of spatial sampling for survey of China's land with remotely sensed data

Science China Earth Sciences 2005年第6期48卷 752-764页

作者： LI Lianfa WANG Jinfeng LIU Jiyuan Institute of Geographic Sciences&Natural Resources Research Chinese Academy of SciencesBeijing 100101China Department of Intelligence Science Peking UniversityBeijing 100087China

In the remote sensing survey of the country land, cost and accuracy are a pair of conflicts, for which spatial sampling is a preferable solution with the aim of an optimal balance between economic input and accuracy of results, or in other words, acquirement of higher ac-curacy at less cost. Counter to drawbacks of previous application models, e.g. lack of compre-hensive and quantitative-comparison, the optimal decision-making model of spatial sampling is proposed. This model first acquires the possible accuracy-cost diagrams of multiple schemes through initial spatial exploration, then regresses them and standardizes them into a unified ref-erence frame, and finally produces the relatively optimal sampling scheme by using the discrete decision-making function (built by this paper) and comparing them in combination with the dia-grams. According to the test result in the survey of the arable land using remotely sensed data, the Sandwich model, while applied in the survey of the thin-feature and cultivated land areas with aerial photos, can better realize the goal of the best balance between investment and accuracy. With this case and other cases, it is shown that the optimal decision-making model of spatial sampling is a good choice in the survey of the farm areas using remote sensing, with its distin-guished benefit of higher precision at less cost or vice versa. In order to extensively apply the model in the surveys of natural resources, including arable farm areas, this paper proposes the prototype of development using the component technology, that could considerably improve the analysis efficiency by insetting program components within the software environment of GIS and RS.

关键词： survey of countrywide land with RS data spatial sampling optimal decision-making model of spatial sampling.

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optimal decision-making of Trans-Provincial Electricity Market Subjects with Risks under Renewable Portfolio Standards

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Energy Engineering 2022年第3期119卷 1141-1167页

作者： HuiWang Yishu Chen Zichao Wu Haocheng Xu School of Economics and Management Shanghai University of Electric PowerShanghai201306China

The randomness and uncertainty of renewable energy generation are expected to significantly change the optimal decision-making of trans-provincial electricity market ***,it is beneficial to optimize the interests of each of these subjects,considering the unpredictable risks of renewable energy under the renewable portfolio standards(RPS)and researching their effects on the optimal decision-making of transprovincial electricity market ***,we develop a trans-provincial trading market mechanism for renewable energy and clarify the electricity supply and demand relation and the green certificates supply and demand relation of trans-provincial ***,under the RPS,we construct a multi-subject game model of the power supply chain that recognizes the risks,and adopt the reverse induction method to discuss the optimum risk-taking judgment of each subject in the trans-provincial electricity ***,we useMATLAB to verify the viability and efficacy of the proposed gamemodel,and obtain a certain reference value for the optimal decision-making of trans-provincial electricity market *** summary,we consider the uncertainty risks of renewable energy under RPS,study the effects of the green certificate price and risk aversion coefficient in the RPS mechanism on the optimal decisionmaking of trans-provincial electricity market subjects,and obtain the changing trends of two different power products and those of different electricity market subjects under the influence of the green certificate price and risk aversion coefficient,which have a certain reference value for studying the factors affecting the optimal decision-making of trans-provincial electricity market subjects.

关键词： Renewable portfolio standards uncertainty risks CVaR method trans-provincial electricity market subjects optimal decision-making

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Self-deception can evolve under appropriate costs

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Current Zoology 2015年第2期61卷 382-396页

作者： Juan Camilo RAMiREZ James A. R. MARSHALL Department of Computer Science University of Sheffield Sheffield S 1 4DP United Kingdom

Apparent biases in decision making by animals, including humans, seem to present an evolutionary puzzle, since one would expect decisions based on biased （unrealistic） information to be suboptimal. Although cognitive biases are hard to diag- nose in real animals （Marshall et al., 2013b）, we investigate Trivers＇ proposal that individuals should self-deceive first in order to better deceive others （Trivers, 2011）. Although this proposal has been scrutinized extensively （Bandura et al., 2011） it has not been formally modelled. We present the first model designed to investigate Trivers＇ proposal. We introduce an extension to a re- cent model of the evolution of self-deception （Johnson and Fowler, 2011）. In the extended model individuals make decisions by taking directly into account the benefits and costs of each outcome and by choosing the course of action that can be estimated as the best with the information available. It is shown that in certain circumstances self-deceiving decision-makers are the most evolutionarily successful, even when there is no deception between these. In a further extension of this model individuals addi- tionally exhibit deception biases and Trivers＇ premise （that effective deception is less physiologically costly with the aid of self-deception） is incorporated. It is shown that under Trivers＇ hypothesis natural selection favors individuals that self-deceive as they deceive others .

关键词： Self-deception Deception Overconfidence Cognitive biases optimal decision-making optimal behavior

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