Optimizing mixture properties of biodiesel production using genetic algorithm-based evolutionary support vector machine

Nowadays, biodiesel is used as one of the alternative renewable energy due to the increasing energy demand. However, optimum production of biodiesel still requires a huge number of expensive and time-consuming laboratory tests. To address the problem, this research develops a novel Genetic Algorithm-based Evolutionary Support Vector Machine (GA-ESIM). The GA-ESIM is an Artificial Intelligence (AI)-based tool that combines K-means Chaotic Genetic Algorithm (KCGA) and Evolutionary Support Vector Machine Inference Model (ESIM). The ESIM is utilized as a supervised learning technique to establish a highly accurate prediction model between the input--output of biodiesel mixture properties; and the KCGA is used to perform the simulation to obtain the optimum mixture properties based on the prediction model. A real biodiesel experimental data is provided to validate the GA-ESIM performance. Our simulation results demonstrate that the GA-ESIM establishes a prediction model with better accuracy than other AI-based tool and thus obtains the mixture properties with the biodiesel yield of 99.9%, higher than the best experimental data record, 97.4%.     

AHP与GA-SVM耦合模型在滑坡预警中的应用*

为了减少滑坡造成的损失,提高滑坡预测的准确性,通过搭建灾害模拟平台获得滑坡的实验数据,在获得多组模拟实验数据后,分析各变量的特性。首先,通过层次分析(Analytic Hierarchy Process,AHP)算法,对滑坡进行危险度划分;然后,通过支持向量机(Support Vector Machine,SVM)建立模型,遗传算法(Genetic Algorithm,GA)再优化SVM参数,提出1种层次分析法与GA-SVM相耦合的模型。研究结果表明:AHP方法划分后的数据,通过GA与SVM结合建立的模型精度较好,实验预测结果与实际结果较为吻合,与单一SVM相比,精度更高,结果更好,更加适用于多变量的复杂非线性滑坡预警。     

Forecasting China’s primary energy demand based on an improved AI model

An improved energy demand forecasting model is built based on the autoregressive distributed lag (ARDL) bounds testing approach and an adaptive genetic algorithm (AGA) to obtain credible energy demand forecasting results. The ARDL bounds analysis is first employed to select the appropriate input variables of the energy demand model. After the existence of a cointegration relationship in the model is confirmed, the AGA is then employed to optimize the coefficients of both linear and quadratic forms with gross domestic product, economic structure, urbanization, and technological progress as the input variables. On the basis of historical annual data from 1985 to 2015, the simulation results indicate that the proposed model has greater accuracy and reliability than conventional optimization methods. The predicted results of the proposed model also demonstrate that China will demand approximately 4.9, 5.6, and 6.1 billion standard tons of coal equivalent in 2020, 2025, and 2030, respectively.     

Post-flooding disaster crop diversity recovery: a case study of Cowpea in Mozambique

To restore food security to a traditional African cropping system following a sudden loss of seed, genetic diversity must be re-established. This study examines the extent to which Cowpea diversity was reinstated two years after a flood disaster in Gaza Province, Mozambique. The contribution that seed from various sources made to the recovery was assessed using semi-structured interviews and morphological and molecular data. Data suggest that diversity had recovered to some extent yet there was evidence of a narrowing of the genetic base, with fewer rare alleles and differences in the distribution of allele frequencies. Although the main channels for accessing seed after the flood were seed relief and markets, these sources contributed to minimal and different diversity. It appears that diversity was regained primarily through social networking in the form of loans or gifts of seed from friends and relatives. The results of the study are discussed in relation to seed relief approaches.     

培养藻类制取生物能源的研究

能源紧张和环境污染是全世界所面临的共同问题,用藻类替代传统作物生产生物能源是生物质能的重要发展方向之一。文章介绍了国内外对藻类培养条件、光生物反应器型式、藻类基因工程、藻细胞收集方法以及能源藻类生产系统的研究成果。研究认为,以藻类为原料生产生物燃料具有良好的发展前景,并指出了今后能源藻类生长的重点研究方向。     

响应面法和神经网络优化Acinetobacter sp. DNS32发酵基质

为了提高阿特拉津降解菌Acinetobacter sp.DNS32的产量,分别采用响应曲面法和基于人工神经网络的遗传算法对阿特拉津降解菌DNS32发酵培养基中3个重要基质成分(玉米粉、豆饼粉、K2HPO4)进行优化研究。响应曲面法确定3种成分的含量为玉米粉39.494 g/L,豆饼粉25.638 g/L和K2HPO43.265 g/L时,预测发酵活菌最大生物量为7.079×108CFU/mL,实测量为7.194×108CFU/mL;人工神经网络结合遗传算法优化确定3种主要成分含量为玉米粉为39.650 g/L,豆饼粉为25.500 g/L,K2HPO4为2.624 g/L时,预测最大值为7.199×108CFU/mL,实测量为7.244×108CFU/mL;最终确定培养基配方:玉米粉为39.650 g/L,豆饼粉为25.500 g/L,K2HPO4为2.624 g/L,CaCO3为3.000 g/L,MgSO4.7H2O和NaCl均为0.200 g/L;优化后阿特拉津降解菌DNS32发酵生物量比优化前提高了36.6%。结果表明,在阿特拉津降解菌DNS32发酵培养基组分优化方面,响应面法和基于人工神经网络的遗传算法都是可行的,基于人工神经网络的遗传算法具有更好的拟合度和预测准确度。     

遗传投影寻踪回归在城市环境质量评价中的应用

引入投影降维的思想,将遗传投影寻踪与回归分析技术运用到城市环境质量评价中。将此技术与神经网络方法进行实例比较,投影寻踪回归方法不但可以合理地作出环境质量的综合评价,而且消除了神经网络方法中类别判断不够精确的影响。     

响应面法和神经网络优化Acinetobactersp．DNS32发酵基质

为了提高阿特拉津降解菌Acinetobactersp．DNS32的产量,分别采用响应曲面法和基于人工神经网络的遗传算法对阿特拉津降解菌DNS32发酵培养基中3个重要基质成分（玉米粉、豆饼粉、K：HPO。）进行优化研究。响应曲面法确定3种成分的含量为玉米粉39．494g／L,豆饼粉25．638g／L和K。HPO。3．265g／L时,预测发酵活菌最大生物量为7．079×10^8CFU／mL,实测量为7．194×10^8CFU／mL;人工神经网络结合遗传算法优化确定3种主要成分含量为玉米粉为39．650g／L,豆饼粉为25．500g／L,K2HPO4为2．624g／L时,预测最大值为7．199×10^8CFU／mL,实测量为7．244×10。CFU／mL;最终确定培养基配方：玉米粉为39．650g／L,豆饼粉为25．500g／L,K2HPO4为2．624g／L,CaCO3为3．000g／L,MgSO4·7H2O和NaCl均为0．200g／L;优化后阿特拉津降解菌DNS32发酵生物量比优化前提高了36．6％。结果表明,在阿特拉津降解菌DNS32发酵培养基组分优化方面,响应面法和基于人工神经网络的遗传算法都是可行的,基于人工神经网络的遗传算法具有更好的拟合度和预测准确度。     

Effects of Riparian Vegetation and Watershed Urbanization on Fishes in Streams of the Mid‐Atlantic Piedmont (USA)1

Abstract: The joint influences of riparian vegetation and urbanization on fish assemblages were analyzed by depletion sampling in paired forested and nonforested reaches of 25 small streams along an urbanization gradient. Nonforested reaches were narrower than their forested counterparts, so densities based on surface area differ from linear densities (based on reach length). Linear densities (based on number or biomass of fish) of American eel, white sucker and tesselated darter, and the proportion of biomass of benthic invertivores were significantly higher in nonforested reaches, while linear densities of margined madtom and the number of pool species were significantly higher in forested reaches. Observed riparian effects may reflect differences in habitat and algal productivity between forested and nonforested reaches. These results suggest that relatively small‐scale riparian restoration projects can affect local geomorphology and the abundance of fish. Dense vegetative cover in riparian zones and similar or analogous habitats in both forested and nonforested reaches, the relatively small scale of the nonforested reaches, and the low statistical power to detect differences in abundance of rare species may have limited the observed differences between forested and nonforested reaches. There was a strong urbanization gradient, with reductions of intolerant species and increases of tolerant species and omnivores with increasing urbanization. Interactions between riparian vegetation type and urbanization were found for blacknose dace, creek chub, tesselated darter, and the proportion of biomass of lithophilic spawners. The study did not provide consistent support for the hypotheses that responses of fish to riparian vegetation would be overwhelmed by urban degradation or insignificant at low urbanization.     

瑞士绿色水电认证对我国水电开发评估的启示

简要介绍了EAWAG"绿色水电认证"的概念、程序和标准要求,分析了我国目前水电站评估中存在的制度上、技术上的缺陷和问题,结合"绿色水电认证"的特点,论证了该认证标准在我国水电站评估中的适宜性:绿色水电认证将管理计划与生态目标有机地结合,为我国水电评估指标体系的构建提供了十分有益的参考;通过绿色电力认证额外增加的发电量作为生态投资,强调电力的生态价值,提供资金改善受影响河道的生态完整性;绿色水电认证标准中关于生态监测的数据要求,能够填补我国目前水电站生态影响评价数据的不足.