Cost estimation of transformer main materials using Artificial Neural Networks

Mehta, H. D.; Patel, Rajesh; Trivedi, Puja

doi:10.1109/nuicone.2012.6493275

Cited by 7 publications

(2 citation statements)

References 5 publications

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“…Several new transformer optimization methods has been published in the recent decades, which methods applied the recent advancements of the numerical computing methods: ssuch as neural networks [143,144], nature inspired evolutionary, genetic algorithms [143][144][145][146][147][148][149][150][151][152][153][154][155][156][157] and metaheuristic type optimization methods combined with FEM [148]. Because of the difficulty of the cost optimization problem, beside the numerical methods, the analytical transformer models was developed further [4,[149][150][151]. However, most of these analytical methods optimizes for the manufacturing not the lifetime cost of the transformer [148], or solves some smaller sub-optimization task [152][153][154].…”

Section: Analytical Cost Optimization Methodsmentioning

confidence: 99%

Evolution and Modern Approaches of the Power Transformer Cost Optimization Methods

Orosz

2019

Period. Polytech. Elec. Eng. Comp. Sci.

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Transformer design is a challenging engineering task, where the different physical fields have to be harmonized together to fulfill the implied specifications. Due to the difficulty of this task, it can be separated into several subproblems. The first subproblem, in the pre-concept phase, during the transformer design is the calculation of the cost optimal key-design parameters, where not only the technical but also the economical parameters have to be considered, as well. This subproblem belongs to the most general branch of the non-linear mathematical optimization problems. This paper presents the main directions of the evolution and trends in the power transformer design. Main directions of the considered research and the future trends in the field of preliminary design transformer optimization methods are summarized.

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Section: Analytical Cost Optimization Methodsmentioning

confidence: 99%

Evolution and Modern Approaches of the Power Transformer Cost Optimization Methods

Orosz

2019

Period. Polytech. Elec. Eng. Comp. Sci.

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“…ANN can be used as a tool to make the mathematical model of cost estimation, so the accuracy of cost estimation become better. Cost estimation based ANN has been developed in Large Scale Project [1] and Transformer Main Materials [2]. Today, most of developed cost estimation software is based on ANN with various method [3][4].…”

Section: Introductionmentioning

confidence: 99%

Neural network method for control valve cost estimation on the EPC project bidding

Putra¹,

Triyono²

2018

SHS Web Conf.

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Cost estimation on the bidding phase is a crucial stage that determines the success of the Engineering, Procurement and Construction (EPC) project. If the cost offered to the client is too high then it could not compete with the other bidder, but if the cost offered are too low it can reduce profit margins and result in losses for the EPC companies. This paper describe the use of Back Propagation Neural Network method to help determine cost estimation. This method is applied specifically to determine control valve cost estimation on the bidding phase so that the retrieved costs will be accurate. When there is no technical and price quotation from vendors as well as the narrowness of the bidding processing time, this method can be an alternative choice to determine the price based on previous vendor quotation. In the future, this method could be developed and applied for other instrumentation equipment such as transmitter, switch, analyzer, control system and others to achieve total cost estimation of instrumentation equipment in EPC bidding proposal.

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Estimation of Core Losses in Three-Phase Dry-Type Transformers Using Adaptive-Network Based Fuzzy Inference Systems (ANFIS)

Kul

Yildiz

Tezcan

2022

Electric Power Components and Systems

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Cost estimation of transformer main materials using Artificial Neural Networks

Cited by 7 publications

References 5 publications

Evolution and Modern Approaches of the Power Transformer Cost Optimization Methods

Evolution and Modern Approaches of the Power Transformer Cost Optimization Methods

Neural network method for control valve cost estimation on the EPC project bidding

Estimation of Core Losses in Three-Phase Dry-Type Transformers Using Adaptive-Network Based Fuzzy Inference Systems (ANFIS)

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