Big data intelligent measuring system for resource environment bearing capacity

Abstract

The invention belongs to the technical field of resource environments, and discloses a big data intelligent measuring system and method for resource environment bearing capacity. The method includes: establishing a big system data acquisition, analysis and integration system in a resource environment-social and economic binary mode; building a multi-level big data framework structure, wherein the big system data acquisition adopts a multi-feature fusion acquisition algorithm; for massive resource environment and social economic data, adopting a local linear embedding algorithm to carry out big data preprocessing, and establishing a big database of a multi-dimensional and multi-scale resource environment complex system; through data statistical analysis, a distributed mining technology and an intelligent deep learning method, establishing an internal strong association relationship between internal multi-level indexes of the complex and large system of the resource environment; adopting a J2EE or. NET technical framework to carry out visual display of intelligent evaluation. A prevention and control system is effectively applied, the timeliness and accuracy of analysis and processing are improved, and disaster loss is reduced to the maximum extent.

Description

technical field [0001] The invention belongs to the technical field of resources and environment, and in particular relates to a big data intelligent measurement system and method for carrying capacity of resources and environment. Background technique [0002] At present, the existing technologies commonly used in the industry are as follows: [0003] With the rapid advancement of urbanization and industrialization, the resource and environmental problems faced will become more and more serious, and the impact on human society will be relatively lagging behind. The determination of the carrying capacity of resources and the environment has become one of the core issues in the study of sustainable development, and the key is to calibrate whether human activities are within the scope of the carrying capacity. [0004] At present, there are many methods for carrying capacity measurement, such as fuzzy evaluation, principal component analysis, set pair analysis, multi-objectiv...

AI Technical Summary

Problems solved by technology

There are two difficult problems in the technical method of resource and environment carrying capacity measurement: ① There are many sources of data in the complex system of resource and environment, which are relatively strong in correlation, and also include structured data and unstructured data such as images and videos. Data Integration Analysis

②Unavoidable subjectivity in measurement and decision-making

In the decision-making process of normative quantity and quality of carrying capacity, the influence of human value orientation and empirical judgment cannot be avoided

③The current research status is mostly based on the quantitative analysis of indicators for evaluation, and there are still deficiencies in the precise analysis and evaluation of space

[0007] (1) There are many sources of data in the complex system of resources and environment, which are highly correlated and include structured data and unstructured data such as images and videos. At present, there is still a lack of integrated analysis of massive data combined with computers or other data operating media

[0008] (2) Inevitable subjectivity in measurement and decision-making

In the decision-making process of the normative quantity and quality of carrying capacity, the influence of human value orientation and empirical judgment cannot be avoided, and there is currently a lack of a system that combines computer measurement and decision-making

[0009] (3) Most of the evaluations are carried out based on the quantitative analysis of indicators, and there is a lack of effective technical means in the precise analysis and evaluation of space. In terms of spatial representation, it affects the decision-making of carrying capacity

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