Using genetic algorithms to evolve a population of topical queries

Systems for searching the Web based on thematic contexts can be built on top of a conventional search engine and benefit from the huge amount of content as well as from the functionality available through the search engine interface. The quality of the material collected by such systems is highly dependant on the vocabulary used to generate the search queries. In this scenario, selecting good query terms can be seen as an optimization problem where the objective function to be optimized is based on the effectiveness of a query to retrieve relevant material. Some characteristics of this optimization problem are: (1) the high-dimensionality of the search space, where candidate solutions are queries and each term corresponds to a different dimension, (2) the existence of acceptable suboptimal solutions, (3) the possibility of finding multiple solutions, and in many cases (4) the quest for novelty. This article describes optimization techniques based on Genetic Algorithms to evolve “good query terms” in the context of a given topic. The proposed techniques place emphasis on searching for novel material that is related to the search context. We discuss the use of a mutation pool to allow the generation of queries with new terms, study the effect of different mutation rates on the exploration of query-space, and discuss the use of a especially developed fitness function that favors the construction of queries containing novel but related terms.     

求解TSP问题的几种算法比较

旅行售货商问题(简称TSP)是离散优化的一个经典的重要问题,对求解算法的研究非常重要。在介绍求解TSP问题的贪婪算法、禁忌搜索算法、模拟退火算法、遗传算法的基本思想之后,提出了相应的算法。针对测试库的四个典型算例,用程序实现这些算法,对这些算法的运行时间和结果进行比较研究。结果表明贪婪算法短时间就可以得出解,禁忌搜索算法与遗传算法的效果相当,模拟退火算法比遗传算法的结果好。     

基于遗传算法的题库选题设计与实现

从遗传算法的应用入手,阐述了遗传算法的相关概念和执行流程,深入研究了遗传算法在题库选题系统中的应用,探讨了初始种群、适应度函数、选择算子、交叉算子、变异算子的设计方法,并给出了关键实现代码。遗传算法为题库选题提供了高效的解决方案,能够取得良好的选题效果。     

问题引导教学法在中职遗传学中的应用

随着课程改革的推进,教学方法也在不断地更新。问题引导法凭借以教师为主导、以学生为主体、以质询为导向、通过合作方式进行探索学习的优点受到多种学科教师的好评。通过在“医学遗传学”课程中的应用,此种教学方法在培养学生的分析能力和理解能力,增强学生的问题意识和学习兴趣方面获得了较好效果。     

山东省滨州市土壤盐渍化空间分布及成因分析

以山东省滨州市为研究区,在“外考察与样品实验分析的基础上,分析该地区土壤盐渍化的空间分布,并对成因进行分析,为该地区盐碱土的治理与利用提供理论依据。     

Genetic Polymorphism of Angiotensin II Type 1 Receptors and Their Effect on the Clinical Outcome of Captopril Treatment in Arab Iraqi Patients with Acute Coronary Syndrome (Mid Euphrates)

Genetic variation in the angiotensin II type 1 receptor (AT1R) has an important effect on the outcome of acute coronary syndrome (ACS) initiated treatment with captopril. This study aims to investigate the impact of genetic polymorphism of AT1R (rs5186 and rs275651) on the ACS outcome in Iraqi patients treated with captopril. A total of 250 Iraqi individuals with ACS were included in this case—control study and they were divided into two study groups; Study group 1 included 125 participants who were prescribed captopril, 25 mg twice daily and study group 2 included 125 participants who received no captopril as part of their ACS treatment (control study). The AT1R gene (rs5186) CC genotype was found to be associated with ST-elevation myocardial infarction (STEMI) (Odd’s ratio (O.R) = 1.2, P = 0.7), while AC was associated with Non-ST-elevation myocardial infarction (NSTEMI) and unstable angina (UA) (O.R = 1.2, P = 0.8). AC genotype is more prone to have Percutaneous coronary intervention (PCI) after ACS attack (O.R = 1.2, P = 0.6). CC genotype had a risk to get less improvement (O.R = 1.6, P = 0.5), so might require higher doses of captopril during acute coronary insult. The AT1R gene (rs275651) AA genotype was associated with UA (O.R = 1.3, P = 0.9). AA and AT genotypes were more prone to have PCI after ACS attack (O.R = 3.9 P = 0.2, O.R = 3.5, P = 0.3 respectively) and thus requiring higher doses of captopril. We conclude that the AT1R rs5186, rs275651 genetic polymorphisms might partially affect the clinical outcome of ACS patients treated with captopril and might have captopril resistance which requires higher doses.     

基于遗传算法的新建给水管网优化设计

遗传算法是一种较新的工程优化算法,将其引入给水管网优化设计,增强了管网设计方案的经济合理性。对给水管网优化设计的数学模型建立,遗传算法的基本原理、实数编码技术、评价函数的建立进行了分析,并用实例验证了其有效性。     

交通运输行业低碳多式联运路径优化研究

交通运输行业是仅次于电力行业的第二大温室气体排放源，近年来各国对其“低碳化”发展的关注不断提高，运输产业如何承担相应的低碳减排责任，积极变革寻求一种绿色低碳的运输方式成为行业发展的热点问题。低碳多式联运作为一种环境友好型的运输模式，通过综合多种运输方式的技术经济优势可以有效降低运输过程中产生的碳排放量，并逐渐被各大运输公司所关注。本文基于成本和时间双重约束下，将二氧化碳排放量纳入到多式联运研究中，通过碳价函数将二氧化碳的排放量换算为二氧化碳的排放成本，形成考虑整个运输过程的总成本，并在设定时间约束下，建立低碳多式联运优化模型，采用遗传算法求解，得出最佳低碳多式联运组合方式和路线，研究对基于企业层面如何建立多重约束下的低碳联运模式进行探索，并提出了相应的政策建议，研究结论对于促进我国交通运输业供给侧低碳结构性改革具有参考意义。     

GSTP1基因Ile105Val多态性与最大运动状态下的心肺表现

人体谷胱苷肽S-转移酶在肺和心血管系统免疫反应方面扮演一定角色,不少研究已经显示谷胱苷肽S-转移酶P1(glutathione S-transferaseP1,GSTP1)基因Ile105Val多态性可能与肺疾病的发生发展相关联,而该多态是否影响正常人体心肺功能少见报道。选取198名健康汉族成年男性,首次对GSTPl基...     

自适应遗传模拟退火的Web日志关联挖掘

提出一种基于自适应遗传模拟退火策略的Web日志关联规则挖掘算法。该算法在遗传模拟退火策略基础上,引入自适应的交叉概率和变异概率,使其具有较强的全局搜索能力,有效地避免了早熟的现象。实验结果证明,该算法能有效地解决Web日志关联规则挖掘问题。