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Neuro-Fuzzy Modeling Techniques in Economics最新文献

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Graphodynamical research methods for complexity of modern stock markets 现代股票市场复杂性的图动力学研究方法
Pub Date : 2016-09-15 DOI: 10.33111/nfmte.2016.152
V. Soloviev, A. Tuliakova
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引用次数: 0
Fuzzy approach to information risks’ measurement in CRM-systems crm系统信息风险度量的模糊方法
Pub Date : 2016-09-15 DOI: 10.33111/nfmte.2016.199
O. Chernyak, Dmytro Sikorskyi
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引用次数: 0
Study of the neural networks overfitting effect on the example of the problem of application scoring 以应用评分问题为例研究了神经网络的过拟合效果
Pub Date : 2016-09-15 DOI: 10.33111/nfmte.2016.003
Halyna Velykoivanenko, Vladislav Korchynskyi, Vika Chernyshova
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引用次数: 0
Selection of neural network architecture for solving problem of borrowers-individuals trustability classification 基于神经网络体系结构的借款人-个人可信度分类选择
Pub Date : 2016-09-15 DOI: 10.33111/nfmte.2016.123
S. Savina, Vladyslav Ben'
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引用次数: 0
Modelling of optimal investment portfolio of diversified business-group under uncertainty 不确定条件下多元化企业集团最优投资组合建模
Pub Date : 2016-09-15 DOI: 10.33111/nfmte.2016.024
T. Kasyanchuk
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引用次数: 0
Complex of evaluation models of investment potential of the country 国家投资潜力综合评价模型
Pub Date : 2016-09-15 DOI: 10.33111/nfmte.2016.093
O. Lukianenko, I. Miroshnychenko
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引用次数: 0
Modeling of crisis transboundary contagion based on a set of neural networks 基于神经网络的危机跨界传染模型
Pub Date : 2016-09-15 DOI: 10.33111/nfmte.2016.180
Inna Strelchenko
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引用次数: 0
Financial time series forecasting: semantic analysis of economic news 金融时间序列预测:经济新闻的语义分析
Pub Date : 2016-09-15 DOI: 10.33111/nfmte.2016.081
K. Kononova, A. Dek
The paper proposes a method of financial time series forecasting taking into account the semantics of news. For the semantic analysis of financial news the sampling of negative and positive words in economic sense was formed based on Loughran McDonald Master Dictionary. The sampling included the words with high frequency of occurrence in the news of financial markets. For single-root words it has been left only common part that allows covering few words for one request. Neural networks were chosen for modeling and forecasting. To automate the process of extracting information from the economic news a script was developed in the MATLAB Simulink programming environment, which is based on the generated sampling of positive and negative words. Experimental studies with different architectures of neural networks showed a high adequacy of constructed models and confirmed the feasibility of using information from news feeds to predict the stock prices.
本文提出了一种考虑新闻语义的金融时间序列预测方法。为了对财经新闻进行语义分析,在劳格兰麦克唐纳大词典的基础上形成了经济意义上的否定词和肯定词的抽样。抽样选取了金融市场新闻中出现频率较高的词语。对于单根单词,它只留下了公共部分,允许在一个请求中覆盖几个单词。采用神经网络进行建模和预测。为了实现经济新闻信息提取过程的自动化,在MATLAB Simulink编程环境下开发了一个基于生成的正负词采样的脚本。不同神经网络结构的实验研究表明,构建的模型具有较高的充分性,并证实了利用新闻源信息预测股票价格的可行性。
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引用次数: 0
Models of market division into trade areas in the fuzzy conditions 模糊条件下贸易区域市场划分模型
Pub Date : 2015-09-15 DOI: 10.33111/nfmte.2015.189
Liudmyla Tarasova, O. Piskunova
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引用次数: 0
Integration of models of logit-regressions as a committee of experts to assess the creditworthiness of borrower 整合逻辑回归模型作为一个专家委员会来评估借款人的信誉
Pub Date : 2015-09-15 DOI: 10.33111/nfmte.2015.154
S. Savina, Vladyslav Ben'
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引用次数: 0
期刊
Neuro-Fuzzy Modeling Techniques in Economics
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