CN-122020240-A - Medical isotope production base evaluation method, system and medium based on big data

CN122020240ACN 122020240 ACN122020240 ACN 122020240ACN-122020240-A

Abstract

The invention discloses a medical isotope production base evaluation method based on big data, which constructs a double-layer space evaluation model of rigid screening-elastic grading, and improves site selection efficiency and scientificity. According to the invention, multi-source space big data are acquired, firstly, the space mask processing is carried out on an evaluation area by utilizing rigid factors such as fault distance, ecological red line and the like, unsuitable units are rapidly removed by a one-ticket overrule mechanism, the safety bottom line of site selection is ensured, and on the basis, the quantitative calculation is carried out on the elastic factors by utilizing a fuzzy five-element relation degree model aiming at a primary selected area. The layering processing technology not only avoids invalid refined calculation on obvious unsuitable areas and greatly improves the data processing efficiency, but also realizes the digitization and the space visualization of the evaluation result by converting the multi-source data into the comprehensive five-element joint coefficients, and effectively solves the technical problems of strong qualitative subjectivity and lack of space dimension support of the traditional site selection method.

Inventors

WU FEIFEI
CHEN HONGXU
ZHANG TING
SU ZIQIANG
KANG JING
LIAN BING
CHEN HAILONG
CUI JINJIANG
DONG YUYANG
CHEN JIA
CHEN JIACHEN

Assignees

中国辐射防护研究院

Dates

Publication Date: 20260512
Application Date: 20251231

Claims (10)

1. A medical isotope production base evaluation method based on big data is characterized by comprising the following steps: Step S1, multi-source space big data of an area to be evaluated are obtained, wherein the multi-source space big data comprise geographic information data, meteorological hydrologic data and real-time radiation monitoring data; S2, constructing a corresponding radiation environment suitability evaluation index system according to the production technology type of the medical isotope, wherein the production technology type comprises a reactor production technology and an accelerator production technology; step S3, carrying out space suitability preliminary screening on the region to be evaluated based on the rigidity factor, and eliminating unsuitable evaluation units through a space mask to obtain a suitability preliminary selected region; Step S4, establishing a fuzzy five-element association degree model, and quantitatively calculating each evaluation unit in the suitability preliminary selection area, wherein the method specifically comprises the steps of obtaining an elastic factor index value of each evaluation unit, selecting a corresponding positive index association degree formula or negative index association degree formula according to index properties, calculating a single index association coefficient, and carrying out weighted summation on the single index association coefficient by utilizing index weights determined by an entropy weight method to obtain a comprehensive five-element association coefficient; And S5, judging the suitability level of the radiation environment of each evaluation unit according to the comprehensive five-membered coefficient, and generating a medical isotope production base site selection recommendation map.
2. The method for evaluating a medical isotope production base based on big data according to claim 1, wherein in the step S2, the rigidity factor is a binary decision index forming an absolute constraint on site selection, and the elasticity factor is a hierarchical decision index having a relative influence on site selection and having a suitability gradient process; The rigidity factors at least comprise distance from an active fault, population density threshold values and ecological red line area distribution, and when any rigidity factor of a certain evaluation unit does not meet a preset threshold value, the evaluation unit is directly judged to be unsuitable and calculation in the step S4 is not carried out.
3. The method for evaluating a medical isotope production base based on big data according to claim 1 or 2, wherein in step S2, the construction of the corresponding radiation environment suitability evaluation index system according to the production technology type of the medical isotope specifically includes: If the production technology type is a reactor production technology, constructing an evaluation index system containing four dimensions of natural foundation, economy and society, ecological influence and radiation environment; If the production technology type is accelerator production technology, an evaluation index system comprising three dimensions of economic and social, ecological influence and radiation environment is constructed, and the economic and social dimension index of the accelerator production technology comprises an industrial chain synergistic benefit index.
4. The medical isotope production base evaluation method based on big data according to claim 1, wherein in the step S4, the grade standard of the fuzzy five-membered degree of contact model is divided into high suitability, medium low suitability and low suitability, the setting S 1 ,S 2 ,S 3 ,S 4 is respectively 4 critical values of the evaluation grade standard, and the calculation formula of the single index coefficient is divided into a positive index degree of contact formula and a negative index degree of contact formula.
5. The big data based medical isotope production base evaluation method according to claim 1, wherein for the forward factors with larger and better values, the S 1 ,S 2 ,S 3 ,S 4 is arranged from big to small, and the forward index association formula is as follows: ; Wherein X i is an index value of a forward factor, i 1 ,i 2 ,i 3 is a difference coefficient between [ -1,1] values, and J is a contrast coefficient.
6. The big data based medical isotope production base evaluation method of claim 5 wherein for the negative factors with smaller and better values, the S 1 ,S 2 ,S 3 ,S 4 is arranged from small to big, and the negative index association formula is as follows: ; X t is an index value of a negative factor, i 1 ,i 2 ,i 3 is a difference coefficient with a value of [ -1,1], and J is a contrast coefficient.
7. The method for evaluating a medical isotope production base based on big data according to claim 1, wherein the step S5 further comprises a step of analyzing a suitability development situation based on a set pair potential: Constructing a comprehensive five-element joint coefficient by using a formula u=a+bi+cj+dk+el, wherein a, b, c, d and e are respectively contact components, respectively correspond to contact components with high suitability to low suitability, and satisfy a+b+c+d+e=1, i, j, k and l are difference coefficients, and the value is [ -1,1] for calculating the algebraic value of the comprehensive five-element joint coefficient u as a set pairing potential; and dividing the development situation into five grades of counter potential, bias counter potential, average potential, bias homopotential and homopotential according to the numerical value interval of the set pair potential so as to predict the suitability dynamic change trend of the medical isotope production base.
8. The big data based medical isotope production base evaluation method of claim 1 wherein the elasticity factors specifically include: The space-class elastic factors comprise atmospheric diffusion capacity and water body exchange rate, and are obtained by collecting space distribution data and used for representing the dilution capacity of environmental medium to radionuclide; and the comprehensive elastic factors comprise economic benefit evaluation and social acceptance, and are obtained by collecting data of a proper time scale, wherein the economic benefit evaluation index comprises internal yield.
9. A system for evaluating suitability of a medical isotope production base radiation environment based on spatial big data support, characterized in that the medical isotope production base evaluation method based on big data of any one of claims 1 to 8 can be performed, comprising: The data acquisition module is used for acquiring multi-source space big data including geographic information data and radiation monitoring data; the index construction module is used for constructing an evaluation index system containing a rigidity factor and an elasticity factor according to a reactor production technology or an accelerator production technology; The region screening module is used for carrying out spatial mask processing on the evaluation region based on the rigidity factor and eliminating unsuitable regions; the model calculation module is used for calling a positive index association degree formula and a negative index association degree formula and calculating the comprehensive five-element association coefficient of the primary selected area; and the evaluation generation module is used for outputting the suitability level of the radiation environment and the site selection distribution diagram according to the comprehensive five-element joint coefficient.
10. A computer-readable storage medium, on which a computer program is stored, characterized in that the computer program, when executed by a processor, implements the steps of the big data based medical isotope production base evaluation method in accordance with any one of claims 1 to 8.

Description

Medical isotope production base evaluation method, system and medium based on big data Technical Field The invention belongs to the field of radiation protection and environmental protection, and particularly relates to a method for evaluating the suitability of a medical isotope production base radiation environment based on space big data support, a system for evaluating the suitability of the medical isotope production base radiation environment based on space big data support and a computer readable storage medium. Background Along with the rapid development of nuclear medicine technology, the medical isotope medium-long-term development planning (2021-2035) clearly indicates that the medical isotope has an irreplaceable effect in diagnosis and treatment of serious diseases such as cardiovascular diseases, malignant tumors and the like. In order to meet the increasing isotope production demands, the orderly development of industry is ensured, and the scientific and reasonable site selection and layout of medical isotope production bases are important. However, the inventor researches find that a plurality of unresolved technical problems still exist in the practical application of the existing production base site selection and environment suitability evaluation technology, and the specific analysis is as follows: firstly, the existing environment suitability evaluation method has obvious defects in a data processing and screening mechanism, and cannot meet the requirements of efficient and accurate site selection in a large-scale area. Conventional evaluation methods, such as global evaluation for a particular region, often treat the evaluation region as a homogeneous whole, ignoring the spatial heterogeneity characteristic within the geospatial space. In the face of complex geographic environments, the prior art lacks of deep fusion and utilization of multi-source space big data such as GIS vector data and real-time radiation monitoring data, and fails to establish an efficient systematic processing flow from macro screening to micro grading. Specifically, the prior art generally lacks a layered screening mechanism that organically combines a "rigid constraint", such as geological faults, ecological red lines, and other one-ticket overrule index, with a "elasticity evaluation", such as economic benefits, environmental capacity, and other gradual change indexes. This results in either ineffective refinement of a large number of significantly unsuitable areas due to lack of rigid prescreening, reducing the efficiency of the evaluation, or failure to accurately identify the optimal microscopic site selection in the prescreened areas due to lack of elastic classification based on large data, resulting in lack of scientific spatial layout guidance of the final site selection results, and difficulty in achieving optimal matching of radiation safety with land utilization. Secondly, the existing evaluation index system lacks pertinence, cannot adapt to the special requirements of the medical isotope production technology, and easily causes 'supply and demand disjoint' of site selection results. Currently, the site selection evaluation of nuclear technology utilizes the project to directly follow the evaluation standard of a nuclear power plant or a general nuclear facility. These standards are mainly focused on extreme safety, such as extreme geological disasters, low population density areas, and are applicable to nuclear power projects with long half-life and high risk. But appear too single or harsh to a medical isotope production base. Medical isotope products, particularly short half-life nuclides, have extremely high requirements on timeliness, and the production base site selection not only needs to consider radiation safety, but also needs to consider economic and social factors such as logistics transportation convenience, distance from a downstream medical institution, industry chain synergistic benefit and the like. In addition, the existing index system often adopts a 'one-cut' mode, and the essential difference of the reactor production technology and the accelerator production technology in terms of environmental influence and economic requirements cannot be distinguished. For example, accelerator production technology has high flexibility and is relatively less affected by natural foundations, and if the severe site selection criteria of the reactor are fully applied, reasonable industrial layout is greatly limited. Therefore, how to construct a set of differential evaluation index system which can ensure radiation safety and also consider economic characteristics of different production processes is another technical problem to be solved urgently at present. Finally, in terms of an evaluation algorithm and a quantization model, a deterministic evaluation method such as a Delphi method, an Analytic Hierarchy Process (AHP) or an entropy value method is mostly adopted in the prior art. When the m