Multi-criteria decision support system for RFS evaluation

被引：0

作者：

Mukhamediev, R. ^{[1
]}

Mustakayev, R. ^{[2
]}

Yakunin, K. ^{[2
]}

Kiseleva, S. ^{[3
]}

Gopejenko, V ^{[4
]}

机构：

[1] Kazakh Natl Tech Univ, Inst Informat & Telecommun Technol, Alma Ata, Kazakhstan

[2] Inst Informat & Commun Technol, Alma Ata, Kazakhstan

[3] Lomonosov Moscow State Univ, Dept Geog, Moscow, Russia

[4] ISMA Univ, Riga, Latvia

来源：

2018 IEEE 12TH INTERNATIONAL CONFERENCE ON APPLICATION OF INFORMATION AND COMMUNICATION TECHNOLOGIES (AICT) | 2018年

关键词：

Decision making support methods; Geo information systems; Intelligent information technologies; Heterogeneous data machine learning; Renewable energy; Spatially distributed resources;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

The Republic of Kazakhstan has significant deposits of fossil fuels and is one of the largest energy producers among the countries of Central Asia. At the same time, Kazakhstan is one of the richest countries of the world in terms of renewable resources, evaluated as 300 to 1000 billion kWh/year. The paper covers developed methodology and software tools for processing of resource-invariant heterogeneous data which could be applied for evaluation of different resources. This work applies the methods of evaluation of renewable energy sources potential that use multi criteria decision making system (MCDM) based on, among others, Bayesian methods.

引用

页码：13 / 18

页数：6

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