为了揭示大中型工业企业技术创新投资的演化行为与规律,构建了一个以差分形式表示的企业技术创新投资经济增长非线性动力学模型。采用差分演化算法对模型进行了参数优化并进行了计算机模拟。主要结论是:1企业的人均研发经费投入与科技活动人员比率对企业技术创新投资系统经济增长的演化行为有着决定性的影响,可以通过调节二者的值来改变系统的演化特性;2对二者的调节应在一定范围内进行;3并不是二者的值越大就必然导致企业人均工业增加值的上升;4当二者的值增大到一定条件会出现系统演化行为的分岔,分岔后会出现两种决然不同的结果,并最终进入混沌状态;5随着二者的值不断增大,系统进入分岔与走向混沌的速度也不断加快。
Abstract
In order to reveal the evolution behavior and law of Enterprises Technological Innovative Investment (ETII), an economic growth nonlinear dynamic model of ETII expressed in a differential form was constructed. A differential evolution algorithm was used to optimize the parameters of the model, and then the computer simulation has been carried out. The main conclusions are as follows: (1) R&D investment per person and the ratio of R&D personnel have the decisively influence on the evolution behavior of economic growth of ETII system in enterprises, and the evolution characteristics of the system could be changed by adjusting the value of these two impact factors. (2) The factors should be adjusted in a certain range by taking the scientific theory as the guideline and foundation. (3) Value increasing of these two impact factors might not inexorably lead to the raise of industrial value per person. (4) When the value of the two factors is increased to some conditions, the bifurcation will be appeared; and following with two totally different results, and finally the system will enter into a chaotic state. (5) With the R&D investment and/or the R&D personnel ratio increasing, the speed for system entering bifurcation and going into chaotic state is faster.
关键词
技术创新投资 /
非线性动力学模型 /
演化行为 /
计算机模拟 /
大中型工业企业
Key words
technological innovative investment /
nonlinear dynamic model /
evolution behavior /
computer simulation /
large and medium-sized industrial enterprises
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参考文献
[1] 黄洁莉, 夏喆, 杨海燕. 企业科技创新混沌动力学模型研究[J]. 科技与管理, 2007, 42(2): 22-24.
[2] 陈功玉. 企业技术创新行为非线性系统的动力学分析[J]. 系统工程, 2005, 23(12):74-78.
[3] R Barro, S Xavier. Economic Growth [M]. New York: McGraw Hill, 1995.
[4] Stokey. Are there limits to growth? [J].International Economic Review, 1998, 39(1): 1-31.
[5] 梁东黎. 宏观经济学[M], 南京大学出版社, 1999: 418-449.
[6] 梁小民. 高等宏观经济学教程[M]. 北京大学出版社, 1993.
[7] 程国平, 汪波, 岳毅宏. 房地产投资系统动力学模型的建立及其长期演化行为研究[J]. 系统工程理论与实践, 2003(10): 65-68.
[8] 唐魁玉. 网络技术创新的非线性动力学分析[J]. 科学学研究, 2002, 20(1): 99-102.
[9] 黄小原. 动态经济系统中的混沌 [J]. 系统工程, 1990, 8(1): 49-50.
[10] Storn, R., Price, K.: Differential Evolution: a Simple and Efficient Adaptive Scheme for Global Optimization over Continuous Spaces . Technical Report TR-95-012, 1995, 8: 22-23.
[11] Zhao, Yongxiang, Xiong, Shengwu, Li, Meifang. Constrained Singleand Multiple-Objective Optimization with Differential Evolution . Third International Conference on Natural Computation, ICNC 2007: 451-455.
[12] 戴晶平. 利用混沌随机函数进行分形图形计算机模拟[J]. 信息技术, 2005(7): 12-13.
[13] 何松林, 戴祖诚, 王开云. 混沌现象的计算机模拟[J]. 昆明师范高等专科学校学报, 2007, 29(4) : 115-116.
[14] 岳毅宏, 韩文秀. 基于系统Lyapunov指数分析的倍周期分岔研究 [J]. 控制与决策, 2002, 17(增刊): 814-816.
基金
2007年国家自然基金项目"分布式创新的机理及其效应研究"(70772074)。