Artificial Neural Network Conventional Fusion Forecasting Model for Natural Gas Consumption

被引：0

作者：

Pradhan, Prabodh Kumar ^{[1
]}

Dhal, Sunil ^{[2
]}

Kamila, Nilayam Kumar ^{[3
]}

机构：

[1] Reg Coll Management, Dept Comp Applicat, Bhubaneswar, India

[2] Sri Sri Univ, Fac Management, Cuttack, Orissa, India

[3] Capital One, Retail & Direct Technol, Wilmington, DE USA

来源：

2018 INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTING, COMMUNICATIONS AND INFORMATICS (ICACCI) | 2018年

关键词：

Natural Gas; Natural Gas Consumption; Consumption factors; DEMAND; REGRESSION;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

One of the most scarcity natural resource in today's world is Natural Gas. Most of the energy extracted from Natural Gas which is a limited resource. An accurate resource consumption planning is an absolute necessity to conserve this natural resource. We proposed an integrated approach of classical least square time series approach with neural network-based prediction model and compare the results with all classical models and the neural network models. The analyzed results show a better improvement over other classical forecasting and neural network models.

引用

页码：2200 / 2205

页数：6

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