The Antibody Network (ABNET), which is a new Artificial Neural Networks (ANN) based on immune principle, has been proved to have good ability of unsupervised and competitive learning in experiments.
抗体网络作为一种新型的基于免疫原理的神经网络模型，已有实验验证了其具有良好的无监督竞争学习能力。
Constructs the description model of environment and obstacle with neural network. Asks for the best path with immune evolution algorithm.
用神经网络构造机器人周围环境及障碍物的描述模型，用免疫进化算法寻找最佳路径。
Correctness and validity of the neural network object forecast algorithm and immune algorithm with evaluated antigen are tested by the simulation of varies examples.
通过对不同情况算例的仿真，验证了神经网络目标预测算法和基于抗原进化免疫算法的正确性和有效性。
A design scheme of optimal RBF fuzzy neural network controller is proposed based on artificial immune principle.
提出了一种基于人工免疫原理的最优r BF模糊神经网络控制器设计方案。
Radial Basis Function (RBF) neural network learning algorithm based on immune recognition principle is proposed.
提出了一种基于免疫识别原理的径向基函数神经网络学习算法。
By introducing the information processing mechanism of artificial immune systems and neural network to CSA, an immune clonal selection algorithm (ICSA) was proposed.
把人工免疫系统和神经网络系统的信息处理机制引入到CSA提出了免疫克隆选择算法。
Aiming at the design difficulty for fuzzy neural network controller, an immune evolutionary algorithm is proposed to design the parameters of a radial basis function fuzzy neural network controller.
针对模糊神经网络控制器难于设计的问题，提出了一种免疫进化算法用于径向基函数模糊神经网络控制器参数的优化设计。
A immune algorithm neural network model for predicting oil gas is presented by means of combining immune algorithm with neural network theory.
将免疫算法与神经网络理论相结合，提出了免疫神经网络预报模型，以预报油库油气浓度。
In order to prevent neural network learning from getting into local extreme point, artificial immune network algorithm was used to optimize neural network's parameters.
为了避免神经网络的学习过程陷入局部极值点，采用人工免疫网络优化神经网络的参数。
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。
Necessary to study new intelligent detection technology, neural network and artificial immune method are the study hot.
需要研究新的智能检测技术，其中神经网络方法和人工免疫方法是研究的热点。
A Radial Basis Function (RBF) neural network learning algorithm based on immune recognition principle is proposed.
提出了一种基于免疫识别原理的径向基函数神经网络学习算法。
A Radial Basis Function (RBF) neural network learning algorithm based on immune recognition principle is studied.
提出了一种基于免疫识别原理的径向基函数神经网络学习算法。
The approach is based on negative selection mechanism of the natural immune system and combined with artificial neural network to be used for monitoring.
该方法是基于生物免疫系统反面选择机理，并结合人工神经网络进行监测的一种方法。
This approach is based on negative selection mechanism of the natural immune system and combined with artificial neural network to be used for monitoring.
该方法是基于生物免疫系统反面选择机理，并结合人工神经网络进行监测的一种方法。
Results show that the immune algorithm neural network model can predict variety rule of oil gas better and has higher accuracy than that of neural network.
结果表明，该智能预报模型能够较好地识别油气扩散的变化规律，预报精度明显高于神经网络模型。
The paper presents an immune clustering RBF neural network (ICRBFNN) model for short-term load forecasting.
提出了一种免疫聚类径向基函数神经网络(ICRBFNN)模型来预测电力系统短期负荷。
In order to detect the main faults well and truly, a new approach of fault detection for gas valves was proposed based on negative selection mechanism of immune system and neural network.
为了能够准确地检测出气阀的主要故障，从免疫系统反面选择机理出发，结合神经网络，提出了基于免疫神经网络的活塞压缩机气阀故障检测的方法。
The immune clone evolutionary(ICE) algorithm is presented to optimize the parameters of the fuzzy neural network(FNN) controller for the complex billet heating process.
针对复杂钢坯加热过程，提出了一种免疫克隆进化模糊神经网络（ICE-FNN）控制算法。首先根据现场样本数据建立过程神经网络模型；
The immune clone evolutionary(ICE) algorithm is presented to optimize the parameters of the fuzzy neural network(FNN) controller for the complex billet heating process.
针对复杂钢坯加热过程，提出了一种免疫克隆进化模糊神经网络（ICE-FNN）控制算法。首先根据现场样本数据建立过程神经网络模型；
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