[1] 郭克莎. 中国经济发展进入新常态的理论根据——中国特色社会主义政治经济学的分析视角[J]. 经济研究, 2016,51(9):4-16
[2] 张承惠. 新常态对中国金融体系的新挑战[J]. 金融研究, 2015,(2):9-15
[3] Moghaddam A. H., Moghaddam M. H., Esfandyari M. Stock Market Index Prediction Using Artificial Neural Network[J]. Journal of Economics, Finance and Administrative Science, 2016,21(41):89-93
[4] Galeshchuk S. Neural Networks Performance in Exchange Rate Prediction[J]. Neurocomputing, 2016,(172):446-452
[5] 潘和平,张承钊. FEPA-金融时间序列自适应组合预测模型[J]. 中国管理科学, 2018,26(6):26-40
[6] 骆晓强,鲍勤,魏云捷,等. 基于多元传导模型的物价指数预测新方法——2018年中国物价展望[J]. 管理评论, 2018,30(1):3-13
[7] Rahimi Z. H., Khashei M. A Least Squares-based Parallel Hybridization of Statistical and Intelligent Models for Time Series Forecasting[J]. Computers & Industrial Engineering, 2018,(118):44-53
[8] 熊志斌. ARIMA融合神经网络的人民币汇率预测模型研究[J]. 数量经济技术经济研究, 2011,28(6):64-76
[9] Klein T., Walther T. Oil Price Volatility Forecast with Mixture Memory GARCH[J]. Energy Economics, 2016,(58):46-58
[10] 林宇,陈粘,陈宴祥. 基于HMM-EGARCH的银行间同业拆放理论市场波动预测研究[J]. 系统工程理论与实践, 2016,36(3):593-603
[11] Chong E., Han C., Park F. C. Deep Learning Networks for Stock Market Analysis and Prediction:Methodology, Data Representations, and Case Studies[J]. Expert Systems With Applications, 2017,83(15):187-205
[12] 朱庆锋,徐中平,王力. 基于模糊综合评价法和BP神经网络法的企业控制活动评价及比较分析[J]. 管理评论, 2013,25(8):113-123
[13] 蔡艳萍,孙夏. 基于BP神经网络的上市商业银行绩效评价体系[J]. 系统工程, 2016,34(12):24-30
[14] Yu F., Xu X. Z. A Short-Term Load Forecasting Model of Natural Gas Based on Optimized Genetic Algorithm and Improved BP Neural Network[J]. Applied Energy, 2014,(134):102-113
[15] Wang L., Zeng Y., Chen T. Back Propagation Neural Network with Adaptive Differential Evolution Algorithm for Time Series Forecasting[J]. Expert Systems with Applications, 2015,42(2):855-863
[16] 任宏,马先睿,刘华兵. 基于GA-BP神经网络的巨项目投人评价的改进研究[J]. 系统工程理论与实践, 2015,35(6):1474-1481
[17] Rather A. M., Agarwal A., Sastry V. N. Recurrent Neural Network and a Hybrid Model for Prediction of Stock Returns[J]. Expert Systems with Applications, 2015,42(6):3234-3241
[18] Qiu M. Y., Song Y., Akagi F. Application of Artificial Neural Network for the Prediction of Stock Market Returns:The Case of the Japanese Stock Market[J]. Chaos, Solitons and Fractals, 2016,(85):1-7
[19] 肖斌卿,杨旸,李心丹,等. 基于GA-ANN的中国金融安全预警系统设计及实证分析[J]. 系统工程理论与实践, 2015,35(8):1928-1937
[20] 刘超,蒋玉洁,马玉洁,等. 新常态条件下中国经济增长预测研究——基于货币政策调控视角[J]. 管理评论, 2018,30(6):28-39
[21] 张炜,范年柏,汪文佳. 基于自适应遗传算法的股票预测模型研究[J]. 计算机工程与应用, 2015,51(4):254-259
[22] 罗勇,陈治亚. 基于改进遗传算法的物流配送路径优化[J]. 系统工程, 2012,30(8):118-122
[23] Huang H. X., Li J. C., Xiao C. L. A Proposed Iteration Optimization Approach Integrating Backpropagation Neural Network with Genetic Algorithm[J]. Expert Systems with Applications, 2015,42(1):146-155
[24] Srinivas M., Patnaik L. M. Adaptive Probabilities of Crossover and Mutation in Genetic Algorithms[J]. IEEE Transaction on Systems, Man and Cybemetics, 1994,24(4):656-667
[25] 张品一,刘超,高扬. 基于协同论的金融产业系统运营状态评价研究[J]. 管理学报, 2016,13(9):1321-1329
[26] 黄群慧. "新常态"、工业化后期与工业增长新动力[J]. 中国工业经济, 2014, (10):5-19
[27] 李扬,张晓晶. "新常态":经济发展的逻辑与前景[J]. 经济研究, 2015, 50(5):4-19
[28] 潘敏. 经济发展新常态下完善我国货币政策体系面临的挑战[J]. 金融研究, 2016, (2):106-122
[29] Louzis D. P., Vouldis A. T., Metaxas V. L. Macroeconomic and Bank-specific Determinants of Non-performing Loans in Greece:A Comparative Study of Mortgage, Business and Consumer Loan Portfolios[J]. Journal of Banking & Finance, 2012,36(4):1012-1027
[30] Chandwani V., Agrawal V., Nagar R. Modeling Slump of Ready Mix Concrete Using Genetic Algorithms Assisted Training of Artificial Neural Networks[J]. Expert Systems with Applications, 2015,42(2):885-893
[31] 师彪,李郁侠,于新花,等. 基于改进粒子群-模糊神经网络的短期电力负荷预测[J]. 系统工程理论与实践, 2010,30(1):157-166
[32] 刘伟,蔡志伟. 我国工业化进程中产业结构升级与新常态下的经济增长[J]. 北京大学学报(哲学社会科学版), 2015,52(3):5-19 |