A Danger-Theory-Based Immune Network Optimization Algorithm
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A Danger-Theory-Based Immune Network Optimization Algorithm
Existing artificial immune optimization algorithms reflect a number of shortcomings, such as premature convergence and poor local search ability. This paper proposes a danger-theory-based immune network optimization algorithm, named dt-aiNet. The danger theory emphasizes that dan
STLR: a novel danger theory based structural TLR algorithm
Artificial Immune Systems (AIS) have long been used in the field of computer security and especially in Intrusion Detection systems. Intrusion detection based on AISs falls into two main categories. The first generation of AIS is inspired from adaptive immune reactions but, the s
An Artificial Immune Network Clustering Algorithm for Mangroves Remote Sensing Image
Because of not needing training samples and performing the classification just according to the inherent similarity of data in the multidimensional space, unsupervised classification method now gets more and more attention by remote sensing data analyst. Duo to the special growth
RBF Neural Networks Optimization Algorithm and Application on Tax Forecasting
Tax plays a significant role in China's rapid economic growth. Therefore it is of particular importance to improve the predictability and accuracy of the tax plan. The tax data is characterized by being so highly nonlinear and coupling that it is difficult to be represented by us
Solution of Feedback Regulation Problems by Application of Network Optimization Algorithms
The paper is devoted to studying general features of nonlinear regulation problems. It is shown, that in the case when the optimal control is determined from the solution of a receding horizon optimal control problem, it may be interpreted as a dynamic network routing problem. Th
A Gaussian adaptive resonance theory neural network classification algorithm applied to supervised land cover mapping using multitemporal vegetation index data
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