| 1. | Study of telecom customer arrear evaluation based support vector machine
基于免疫进化支持向量机的年用电量预测 |
| 2. | Numerical modeling on seepage in side slope based on immune evolution algorithm
基于免疫进化规划算法的边坡岩体渗流数值模拟 |
| 3. | The optimal flow assignment of computer communication networks based on chaos immune evolutionary programming
基于混沌免疫进化规划的计算机通信网最优流量分配 |
| 4. | Abstract by use of immune evolutionary algorithm , a new optimal method of fuzzy controller was presented
摘要利用免疫进化算法，提出了一种新的模糊控制器优化设计方法。 |
| 5. | A novel fussy clustering method based on immune evolutionary algorithm ( iefcm ) was presented to solve fuzzy edge detection problems in image processing
摘要针对图像处理中的模糊边缘检测问题，提出一种免疫进化模糊聚类算法。 |
| 6. | The immune evolutionary algorithm ( iea ) is a new optimization algorithm with many features developed on the basis of the existing evolutionary algorithm
摘要免疫进化算法是在现有进化算法的基础上发展起来的一种新的优化算法，其具有许多独特的性能。 |
| 7. | The immune algorithm ( ia ) has the capacity of global optimization and is better than traditional genetic algorithm in searching efficiency . the detailed ia " s steps to solve the problem are given
免疫算法具有比遗传算法更加优良的全局寻优能力，本文给出了采用免疫进化算法求解数据最简属性集的步骤。 |
| 8. | The theoretical analysis and many simulations show that immune evolutionary algorithms are not on ; feasible but also effective and are conducive to alleviating the degeneration phenomenon in the original algorithms , thus greatly increasing the converging speed
理论分析和仿真研究表明，免疫进化算法不仅是有效的，而且是可行的，并且可以较好地解决原进化算法中出现的退化问题。 |
| 9. | In this paper , the advantages and limitations of machine learning algorithm that is used for dealing with the definite and obscured knowledge are given , and also some new ideas are proposed , the research works are as follows , 1
本文分析了传统方法(即处理确定性信息的机器学习方法)在入侵检测领域中的优势和不足，并以此为基础，结合粗糙集理论与免疫进化算法，做出了如下创新： 1 |
| 10. | The results show the improved aca can be used to solve the continued problem , and the formula whose parameter is optimized by the improved aca can simulate the primary data better than those whose parameter are optimized by other optimizing methods except the immune evolutionary algorithm ( iea ) , and the improved aca can get almost the same result with less optimization scale and shorter optimization time than iea
结果表明，改进的蚂蚁算法可以成功用于暴雨强度公式的参数优化，并且在实验采用的各种优化算法优化参数得到的暴雨强度公式拟合原始数据的效果比较中只有免疫进化算法在优化过程中迭代次数和迭代规模都要大得多的情况下才和改进的蚂蚁算法差不多，而比其它的优化方法都要好。 |
