Aiming at measuring path planning by using peak value, neural network predictor based on parameter model is presented.
针对峰值法中测量路径规划问题，提出了基于参数模型学习的神经网络预测器。
A new approach to complete coverage path planning for mobile robots, which integrates biologically inspired neural network, rolling window and heuristic searching, is presented.
基于生物激励神经网络、滚动窗口和启发式搜索，提出了一种新的完全遍历路径规划方法。
Finally researches the path planning of robot, applies both neural network and immune evolution algorithm to the path planning of robot.
最后对机器人的路径规划进行了研究，将神经网络和免疫进化算法共同应用于机器人的路径规划。
Next, improves one three dimensional robot path planning environment prototype system kind based on the neural network, prepares the precise sufficiency function for the mixed algorithm.
其次改进了一种基于神经网络的三维机器人路径规划环境原型系统，为混合路径规划算法的提出准备了较精确的适应度函数。
Next, improves one three dimensional robot path planning environment prototype system kind based on the neural network, prepares the precise sufficiency function for the mixed algorithm.
其次改进了一种基于神经网络的三维机器人路径规划环境原型系统，为混合路径规划算法的提出准备了较精确的适应度函数。
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