Real estate valuation method and system based on neural network statistic model
The present invention provides a real estate valuation system based on a neural network statistic model. The system comprises a training unit, a neural network unit and an evaluation unit. The evaluation unit quantizes the grade of the influence factor of a to-be-estimated property so as to obtain t...
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| creator | LIU XIAOJUAN FANG SHAOYUN PENG MINGFENG YANG DINGJIN GUO YOU HE RUI TANG YONG ZHANG HENG |
| description | The present invention provides a real estate valuation system based on a neural network statistic model. The system comprises a training unit, a neural network unit and an evaluation unit. The evaluation unit quantizes the grade of the influence factor of a to-be-estimated property so as to obtain the quantized value of the influence factor of the to-be-estimated property according to a quantization standard. The training unit stores the preset parameters of each neural network. In each neural network, the quantized value of the influence factor of the to-be-estimated property is adopted as an input variable, so that the evaluated value of each neural network for the to-be-estimated property is obtained. The evaluation unit multiplies the value of the to-be-estimated property evaluated by each neural network by a preset weight value so as to obtain the final evaluated value of the to-be-estimated property. According to the technical scheme of the invention, neural networks are determined according to administ |
| format | Patent |
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The system comprises a training unit, a neural network unit and an evaluation unit. The evaluation unit quantizes the grade of the influence factor of a to-be-estimated property so as to obtain the quantized value of the influence factor of the to-be-estimated property according to a quantization standard. The training unit stores the preset parameters of each neural network. In each neural network, the quantized value of the influence factor of the to-be-estimated property is adopted as an input variable, so that the evaluated value of each neural network for the to-be-estimated property is obtained. The evaluation unit multiplies the value of the to-be-estimated property evaluated by each neural network by a preset weight value so as to obtain the final evaluated value of the to-be-estimated property. 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The system comprises a training unit, a neural network unit and an evaluation unit. The evaluation unit quantizes the grade of the influence factor of a to-be-estimated property so as to obtain the quantized value of the influence factor of the to-be-estimated property according to a quantization standard. The training unit stores the preset parameters of each neural network. In each neural network, the quantized value of the influence factor of the to-be-estimated property is adopted as an input variable, so that the evaluated value of each neural network for the to-be-estimated property is obtained. The evaluation unit multiplies the value of the to-be-estimated property evaluated by each neural network by a preset weight value so as to obtain the final evaluated value of the to-be-estimated property. 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| language | chi ; eng |
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| subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES PHYSICS SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR |
| title | Real estate valuation method and system based on neural network statistic model |
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