A CBR-based power engineering cost estimation method

2021 ◽  
Author(s):  
Li Zhou ◽  
Qixin Wang ◽  
Li Ma ◽  
Fangchao Ke
2021 ◽  
Vol 48 (4) ◽  
pp. 3-3
Author(s):  
Ingo Weber

Blockchain is a novel distributed ledger technology. Through its features and smart contract capabilities, a wide range of application areas opened up for blockchain-based innovation [5]. In order to analyse how concrete blockchain systems as well as blockchain applications are used, data must be extracted from these systems. Due to various complexities inherent in blockchain, the question how to interpret such data is non-trivial. Such interpretation should often be shared among parties, e.g., if they collaborate via a blockchain. To this end, we devised an approach codify the interpretation of blockchain data, to extract data from blockchains accordingly, and to output it in suitable formats [1, 2]. This work will be the main topic of the keynote. In addition, application developers and users of blockchain applications may want to estimate the cost of using or operating a blockchain application. In the keynote, I will also discuss our cost estimation method [3, 4]. This method was designed for the Ethereum blockchain platform, where cost also relates to transaction complexity, and therefore also to system throughput.


2014 ◽  
Vol 4 (1) ◽  
pp. 3-12 ◽  
Author(s):  
Jun Liu ◽  
Jian-Zhong Qiao

Purpose – Due to the limitation of acknowledgment, the complexity of software system and the interference of noises, this paper aims to solve the traditional problem: traditional software cost estimation methods face the challenge of poor and uncertain inputs. Design/methodology/approach – Under such circumstances, different cost estimation methods vary greatly on estimation accuracy and effectiveness. Therefore, it is crucial to perform evaluation and selection on estimation methods against a poor information database. This paper presents a grey rough set model by introducing grey system theory into rough set based analysis, aiming for a better choice of software cost estimation method on accuracy and effectiveness. Findings – The results are very encouraging in the sense of comparison among four machine learning techniques and thus indicate it an effective approach to evaluate software cost estimation method where insufficient information is provided. Practical implications – Based on the grey rough set model, the decision targets can be classified approximately. Furthermore, the grey of information and the limitation of cognition can be overcome during the use of the grey rough interval correlation cluster method. Originality/value – This paper proposed the grey rough set model combining grey system theory with rough set for software cost estimation method evaluation and selection.


2019 ◽  
Vol 126 ◽  
pp. 5-14
Author(s):  
Anna Gobis ◽  
Kazimierz Jamroz ◽  
Łukasz Jeliński

The transport infrastructure management should be in line with sustainable development. Actions and activities that combine the environmental, social, and infrastructure expenditures optimally should be undertaken. The article presents a concept of life-cycle thinking that resolves these problems. The life cycle cost estimation method is a practical tool for managing transport infrastructure. The LCC analysis mustn’t generate more work than the benefits of it. Therefore appropriate assumptions should be made in constructing the method. The method assumes basic assumptions, taking into account the extensive scope of the research problem: transport infrastructure. The result of this article is a proposed mathematical model for estimating life-cycle costs. In the end, the practical use of the proposed methodology for determining the cost of the horizontal marking is provided.


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