智能法院信息化发展水平系统评价的神经网络方法

dan Zhang dan ZHANG, Ting-Jie Lu Dan Zhang, Wenyu Zhang Tingjie Lu, Chenxing Yang Wenyu Zhang
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引用次数: 0

摘要

信息化发展水平的系统评价(IDL)是顺应数字化、网络化、智能化发展趋势,关注信息化业务能力形成的一种评价。多年来,国内外学者对信息化评价方法进行了广泛的研究。但传统的评价方法存在机制设计复杂、度量转换不可靠、指标相对重要性难以获取、评价过程复杂、计算量大等缺陷。本文尝试将神经网络方法引入到信息系统评价中,并采用极限学习机(ELM)算法建立评价模型。以智能法院系统的评估为例,对模型进行仿真和测试,结果表明,基于神经网络的信息化系统评估模型更适用于大规模的评估指标,并且通过不断增加学习样本,客观上提高了评估的准确性,有效避免了人为的主观因素,具有先进性、准确性和便捷性等优势特点。
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A Neural Network Method for Systematic Evaluation of Informatization Development Level in Smart Court Construction
The systematic evaluation of informatization development level (IDL) is an evaluation that follows the development trend of digitization, networking and intelligence, and focuses on the formation of business capabilities of informatization. Research on informatization evaluation methods has been extensively studied by both domestic and international academics over the years. However, traditional evaluation methods suffer from flaws like complex mechanism design, unreliable metric conversion, difficulty obtaining the relative importance of indexes, complex evaluation process, and high computational volume. This paper attempts to introduce the neural network method into the information system evaluation, and uses the Extreme Learning Machine (ELM) algorithm to establish the evaluation model. The evaluation of the smart court system is used as an example to simulate and test the model, and the results show that the neural network-based evaluation model of informatization system is more applicable to large-scale evaluation indexes, and by continuously increasing the learning samples, it objectively improves the accuracy of evaluation, effectively avoids human subjective factors, and has the advantageous features of advanced, accurate and convenient.  
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