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Exploring the suitability of artificial intelligence for establishing criteria for prequalification of highway contractors in Sri Lanka

机译:探索人工智能在建立斯里兰卡公路承包商资格预审标准中的适用性

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The extent of the successfulness of a construction project is highly influential on the selected contractor. The decision process has been made easier for the client with the use of prequalification. The selection criteria used for the prequalification are characterized by the co-existence of both quantitative and qualitative information. Therefore in such scenario, it become difficult to analyze the information by decision maker due to the complexity bound to the process. Hence, to improve the reliability and efficiency of the decision being made, it is essential to identify suitable decision support system for the process. The use of Artificial Intelligence (AI) techniques to the prequalification process helps to eliminate the complexity on the decision making of the prequalification process. This research demonstrates the practicality and the suitability on adopting Artificial Neural Network (ANN), Case-based Reasoning (CBR) and Knowledge Based Experts Systems (KBES) to the highway contractor prequalification in Sri Lanka. Therefore, the findings of this research conclude that with the help on identified prequalification model and the identified AI techniques, Sri Lanka can have an effective and efficient mechanism on Highway contractor prequalification.
机译:建设项目的成功程度对所选承包商影响很大。通过使用资格预审,客户的决策过程变得更加容易。用于资格预审的选择标准以定量和定性信息的并存为特征。因此,在这种情况下,由于过程的复杂性,决策者难以分析信息。因此,为了提高决策的可靠性和效率,必须为该过程确定合适的决策支持系统。在资格预审过程中使用人工智能(AI)技术有助于消除资格预审过程决策中的复杂性。这项研究证明了在斯里兰卡的公路承包商资格预审中采用人工神经网络(ANN),基于案例的推理(CBR)和基于知识的专家系统(KBES)的实用性和适用性。因此,本研究的结论是,在确定的资格预审模型和确定的AI技术的帮助下,斯里兰卡可以对公路承包商进行资格预审具有有效的机制。

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