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Application of adaptive neuro fuzzy inference system in demand forecasting for power engineering company

机译:自适应神经模糊推理系统在电力工程公司需求预测中的应用

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摘要

To enhance the commercial competitive advantage in a constantly fluctuating business environment, an organisation has to make the right decisions in time depending on demand information. Therefore, estimating the demand quantity for the next period most likely appears to be crucial. Forecasting becomes a crucial process for manufacturing companies to effectively guiding several activities, and research has devoted particular attention to this issue. The objective of the paper is to propose a new forecasting mechanism which is modelled by adaptive neuro-fuzzy inference system (ANFIS) techniques to manage the fuzzy demand with incomplete information. ANFIS is utilised to harness the power of the fuzzy logic and artificial neural networks (ANN) through utilising the mathematical properties of ANNs in tuning rule-based fuzzy systems that approximate the way human's process information. To accredit the proposed model, it is implemented to forecast the demand of distribution transformer of a power engineering company of Bangladesh.
机译:为了在不断变化的商业环境中增强商业竞争优势,组织必须根据需求信息及时做出正确的决定。因此,估计下一个时期的需求量似乎很关键。预测已成为制造公司有效指导多项活动的关键过程,研究对此问题特别关注。本文的目的是提出一种新的预测机制,以自适应神经模糊推理系统(ANFIS)技术为模型,以管理信息不完整的模糊需求。 ANFIS通过在基于规则的模糊系统中调整近似人的过程信息的方式,利用ANN的数学特性,来利用模糊逻辑和人工神经网络(ANN)的功能。为了对提议的模型进行认证,该模型用于预测孟加拉国一家电力工程公司的配电变压器的需求。

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