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Cold regions residential building energy evaluation

Author: LongMin
Tutor: LiuJianBing;WenYongLe
School: Jiangxi University of Technology
Course: Project Management
Keywords: Residential energy conservation Index system Fuzzy Comprehensive Evaluation Comprehensive energy consumption Artificial Neural Networks
CLC: TU201.5
Type: Master's thesis
Year: 2010
Downloads: 201
Quote: 0
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Abstract


Currently, the building energy efficiency has been the formation of a worldwide trend, but late, the low level of building energy efficiency in China work time, the proportion of total energy consumption in the building energy consumption is growing year by year, as the socio-economic prosperity. Building energy consumption is an important part of humanity's total energy consumption is an important source of pollution. Increasing energy consumption growing energy crisis also caused serious environmental pollution, has become the climate becomes abnormal phenomenon caused ecological damage direct factor seriously jeopardize the survival of our ecological environment. Our biggest problem in building energy efficiency work is low energy efficiency, architectural interior does not give people a better comfort. In response to this situation, this paper, \However, our current building energy efficiency evaluation of the situation, there are still many of the following deficiencies: first, building energy efficiency evaluation of the lack of universal identity building energy evaluation system and weight distribution; Second, building energy evaluation is a very systematic research topic, the evaluation process there must be the main objective judgment, however, the subjective judgment inherent uncertainty and incomplete. In view of the above building energy efficiency evaluation system there are still problems, to achieve the goal of sustainable development more effectively promote the construction of the cold regions of energy-saving technologies and standards, established five benchmarks layer evaluation index system: building energy consumption, building design, construction, maintenance of the structure, building heating and air conditioning systems, building technology, economic. Level through a combination of qualitative and quantitative analysis, to further determine the evaluation index weight fuzzy comprehensive evaluation method, according to the evaluation criteria, the establishment of a residential energy conservation evaluation system model. Meanwhile, the introduction of artificial neural network theory of knowledge, in the MATLAB language environment, combined with this paper, the use of the residence building energy evaluation grade evaluation factor system based on artificial neural network theory knowledge living energy saving evaluation model was constructed, and the preparation of the neural network evaluation program by the two methods in the actual engineering use and compare the obtained neural network evaluation method is more effective to solve the housing problem of energy-saving evaluation conclusions, and neural network evaluation method is relatively convenient to use. Further promote and extend the theoretical study of the evaluation system.

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CLC: > Industrial Technology > Building Science > Architectural design > General issues > Design principles, the principles and management > Building energy efficiency design
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