基于人工神经网络的秀丽隐杆线虫趋温性行为的建模与仿真

Modeling and simulating thermotaxis behavior of Caenorhabditis elegans based on artificial neural network

为了模拟秀丽隐杆线虫的趋温性行为,提出一种通过人工神经网络对秀丽隐杆线虫的趋温性行为进行建模的方法,并进行实验仿真。首先,建立秀丽隐杆线虫的运动模型;然后,通过设计非线性函数逼近线虫趋温性的运动逻辑,实现运动速度和偏向角度的改变功能;最后,通过人工神经网络对该非线性函数进行学习,从而在Matlab环境中对上述过程进行实验仿真,模拟出了秀丽隐杆线虫的趋温性行为。实验结果表明,在更接近生物体本质的条件下,反馈(BP)神经网络比径向基函数(RBF)神经网络能更好地模拟线虫的趋温性行为。同时也表明所提方法能够很好地模拟秀丽隐杆线虫的趋温性行为,在一定程度上揭示了线虫趋温性的实质,理论上支持了爬虫机器人的趋温性研究。

To research the thermal behavior of Caenorhabditis elegans（ C. elegans）, a new method was proposed to model and simulate the thermal behavior of C. elegans based on the artificial neural network. Firstly, the motion model of the nematode was established. Then, a nonlinear function was designed to approximate the movement logic of the thermotaxis of the nematode. Thirdly, the speed and the orientation change capabilities were implemented, and these capabilities had been realized by the artificial neural network. Finally, the experimental simulation was carried out in the Matlab environment, and the thermal behavior of the nematode was simulated. The experimental results show that Back Propagation（ BP） neural network can simulate the thermal behavior of C. elegans better than Radical Basis Function（ RBF） neural network. The experimental results also demonstrate that the proposed method can successfully model the thermal behavior of C. elegans, and reveal the essence of the thermotaxis of C. elegans to some extent, which theoretically supports the research on the thermotaxis of the crawling robot.