Pesticide residue data-oriented multidimensional cross-over analysis method and system

Abstract

The invention discloses a pesticide residue data-oriented multidimensional cross-over analysis method. According to the method, a double multidimensional data correlation storage model based on doublecubes is constructed, double multidimensional cross-over data analysis treatment is conducted according to pesticide residue data, multidimensional analysis query and analysis are conducted among multiple data subsets, and detection identification of abnormal values is carried out; a pesticide residue data-oriented multidimensional over-cross analysis system is achieved by utilizing the multidimensional cross-over analysis method. The system includes an information collecting module, a data warehouse module, a data analysis module and an automatic report generating module. Through exception detection for identifying abnormal data values, data is more comprehensively analyzed, and an online analysis service is provided for pesticide residue risk evaluation and scientific management and usage of pesticide.

Description

technical field [0001] The invention relates to an analysis method of multi-dimensional, hierarchical and associated data, in particular to a multi-dimensional cross-analysis method and system for pesticide residue data. Background technique [0002] Pesticide residues are one of the main factors leading to food safety problems. For this reason, the food safety testing departments of the country and various provinces and cities have to test the pesticide residues in agricultural products every year. There are multiple dimensions such as time, sampling location, and limit standards. The data volume is large and interrelated, and some dimensions also have hierarchical characteristics. How to conduct all-round statistical analysis and early warning of such data and provide data support for government decision-making is an urgent problem to be solved. The current pesticide residue data analysis methods mainly use Excel, SPSS and other data analysis software to perform relativel...

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Problems solved by technology

The current pesticide residue data analysis methods mainly use Excel, SPSS and other data analysis software to perform relatively simple mathematical statistics on the data, and it is difficult to achieve cross and correlation statistical analysis, and the statistical results are mainly expressed by some independent data tables and statistical charts. Difficult to meet the above statistical analysis needs

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