This paper presents a method to simulate growth phenomena, and its application to the modeling of complex organic shapes (e.g., plants organs) and folded surfaces. Our main contri...
Abstract. Recent studies have demonstrated the possibility to build genetic regulatory networks that confer a desired behavior to a living organism. However, the design of these ne...
Abstract. This paper investigates the construction of a wide class of singlehidden layer neural networks (SLNNs) with or without tunable parameters in the hidden nodes. It is a cha...
Kang Li, Jian Xun Peng, Minrui Fei, Xiaoou Li, Wen...
Point estimates of the parameters in real world models convey valuable information about the actual system. However, parameter comparisons and/or statistical inference requires de...
The success of evolutionary algorithms (EAs) depends crucially on finding suitable parameter settings. Doing this by hand is a very time consuming job without the guarantee to ...
: Linear Parameter Varying(LPV) systems appear in a form of LTI state space representations where the elements of the A(ρ), B(ρ), C(ρ) matrices can depend on an unknown but at a...
—The F2 (Force Field) method is a novel approach for multi-robot motion planning and collision avoidance. The setting of parameters is however vital to its performance. This pape...
Dalong Wang, Ngai Ming Kwok, D. K. Liu, Haye Lau, ...
Network performance measurement and prediction is very important to predict the running time of high performance computing applications. The LogP model family has been proven to b...
We present a machine learning methodology (models, algorithms, and experimental data) to discovering the agent dynamics that drive the evolution of the social groups in a communit...
Hung-Ching Chen, Mark K. Goldberg, Malik Magdon-Is...
–- To obtain optimal location area (LA) partitioning in cellular radio networks is important since it maximizes the usable bandwidth to support services. However, we feel that th...
Yong Huat Chew, Boon Sain Yeo, Daniel Chien Ming K...