Chun Tian Cheng

TL;DR: A novel chaos genetic algorithm based on the chaos optimization algorithm (COA) and genetic algorithm (GA), which makes use of the ergodicity and internal randomness of chaos iterations, is presented to overcome premature local optimum and increase the convergence speed of genetic algorithm.

TL;DR: In this paper, a new methodology of multiple criteria data envelopment analysis (MCDEA), which can address both qualitative and quantitative criteria, is presented, and a case study on the selection of dam location illustrates the effectiveness of the proposed methodology.

TL;DR: A hybrid neural network model was proposed, which integrated characteristics decomposition units, and a dynamic spline interpolation unit into the multiple ATNNs, which is quite effective in MS prediction, especially for single-factor time series.

TL;DR: In this article, an overview of the China's hydropower, analyses the new challenges that it faces, highlights the key scientific and technological issues that need to be solved, and pinpoints that the solution of these problems will be the key to the realization of energy saving and emission reduction by China in 2020.

TL;DR: The current method integrates the two parts of Xinanjiang rainfall–runoff model calibration together, simplifying the procedures of model calibration and validation and easily demonstrated the intrinsic phenomenon of observed data in integrity.