基于GA_XGBoost模型的大学生科研能力预测问题研究

科学评价大学生科研创新能力对我国科研水平的提高具有重要意义.采用机器学习模型来预测大学生科研能力可以起到良好的效果,提出一种GAXGBoost模型来实现对大学生的科研能力预测.此模型是以Xgboost算法为基础,然后充分利用遗传算法的全局搜索能力自动搜索Xgboost最优超参数,避免了人为经验调参不准确的缺陷,最后采用精英选择策略以此确保每一轮都是最佳的进化结果.通过分析表明,所采用的GAXGBoost模型在大学生科研能力预测的结果中具有很高的精度,将此模型与Logistic Regression、Random Forest、SVM等模型进行对比,GAXGBoost模型的预测精度最高.     

A volatolomic approach using cerumen as biofluid to diagnose bovine intoxication by Stryphnodendron rotundifolium

An innovative volatolomic approach employs the detection of biomarkers present in cerumen (earwax) to identify cattle intoxication by Stryphnodendron rotundifolium Mart., Fabaceae (popularly known as barbatimão). S. rotundifolium is a poisonous plant with the toxic compound undefined and widely distributed throughout the Brazilian territory. Cerumen samples from cattle of two local Brazilian breeds (‘Curraleiro Pé-Duro’ and ‘Pantaneiro’) were collected during an experimental intoxication protocol and analyzed using headspace (HS)/GC–MS followed by multivariate analysis (genetic algorithm for a partial least squares, cluster analysis, and classification and regression trees). A total of 106 volatile organic metabolites were identified in the cerumen samples of bovines. The intoxication by S. rotundifolium influenced the cerumen volatolomic profile of the bovines throughout the intoxication protocol. In this way, it was possible to detect biomarkers for cattle intoxication. Among the biomarkers, 2-octyldecanol and 9-tetradecen-1-ol were able to discriminate all samples between intoxicated and nonintoxicated bovines. The cattle intoxication diagnosis by S. rotundifolium was accomplished by applying the cerumen analysis using HS/GC–MS, in an easy, accurate, and noninvasive way. Thus, the proposed bioanalytical chromatography protocol is a useful tool in veterinary applications to determine this kind of intoxication.     

光码分多址系统中光学相关接收机判决阈值的分析

介绍了光码分多址系统中常用地址码（一维扩时码、二维码和三维码）的特点，并对它们各自的互相关均值和方差进行了理论分析。基于非相干光码分多址系统中光学相关接收机的基本原理，结合不同的用户地址码，对系统误码率性能进行了分析，得到了接收机最佳判决阈值与地址码基本特性参数和系统同时用户数间的关系。最后，给出了数值仿真结果。结果表明，对于采用特定地址码的光码分多址系统，只有选择合适的接收机判决阈值，系统的误码率性能才能达到最佳。研究结果对光码分多址系统中接收机判决阈值的选取具有一定的参考作用。     

Toward Fuzzy Optimization without Mathematical Ambiguity

Fuzzy programming has been discussed widely in literature and applied in such various disciplines as operations research, economic management, business administration, and engineering. The main purpose of this paper is to present a brief review on fuzzy programming models, and classify them into three broad classes: expected value model, chance-constrained programming and dependent-chance programming. In order to solve general fuzzy programming models, a hybrid intelligent algorithm is also documented. Finally, some related topics are discussed.     

基于遗传算法和指标满意度求解的第三方物流企业物流中心选址方法

本利用AHP和模糊综合评价法评价物流中心选址的定性指标、用量化选址模型结合遗传算法计算定量指标，再藉助指标满意度求解把定性和定量的指标进行综合，从而为决策对物流中心选址做出科学的决策提供支持。     

基于实数编码的免疫遗传算法研究

针对标准遗传算法(SGA)搜索效率低、收敛速度慢等缺陷，在免疫遗传算法的基础上提出了基于实数编码的免疫遗传算法(RIGA)。研究表明，RIGA对SGA的改进是有效可行的，显示出稳健的全局优化、计算量少而解的精度高等特点，具有较高的应用价值。     

达草灭对莱茵衣藻(Chlamydomonas reinhardtii) 品系遗传后效应的研究

通过将莱菌衣藻（Chlamydomonas reinhardtii）6种达草灭抗性突变株分别与野生型株、丧失合成叶绿素b能力的cbnI-43等基因突变株和精氨酸依赖型突变株杂交对其后代进行四分析与随机分析，发现在Nfr-4-Nfr-7突变株中达草灭抗性状只有单一核基因遗传的性质，而在Nfr-1、Nfr-3～Nfr-7抗性株的抗性性状都是由同一个nfr-1基因（norflurazon resisanse）的突变所决定的，而Nfr-4抗性株的抗性性状是由另一滚突变等位基因nfr-2所决定的。在Nfr-1和Nfr-3抗性株中除了nfr-1基因的突变还有nfr-3基因突变的参与。     

Robust handling of non‐linear constraints for GA optimization of aerodynamic shapes

A new approach to the robust handling of non‐linear constraints for GAs (genetic algorithms) optimization is proposed. A specific feature of the approach consists of the change in the conventional search strategy by employing search paths which pass through both feasible and infeasible points (contrary to the traditional approach where only feasible points may be included in a path). The method (driven by full Navier–Stokes computations) was applied to the problem of multiobjective optimization of aerodynamic shapes subject to various geometrical and aerodynamic constraints. The results demonstrated that the method retains high robustness of conventional GAs while keeping CFD computational volume to an acceptable level, which allowed the algorithm to be used in a demanding engineering environment. Copyright © 2004 John Wiley & Sons, Ltd.     

基于改进遗传算法的布局优化子问题

本针对子问题，构造了布局子问题(关于同构布局等价类)的改进遗传算法。将该算法应用于二维布局优化子问题，数值实验表明该算法能够在很好地保持图元的邻接关系的前提下找到子问题的最优解。由于布局优化问题可分解为有限个子问题，所以利用该算法可以找到整个布局优化问题的全局最优解。