Estimation of wear performance of AZ91 alloy under dry sliding conditions using machine learning methods

The wear behavior of AZ91 alloy was investigated by considering different parameters,such as load(10−50 N),sliding speed(160−220 mm/s)and sliding distance(250−1000 m).It was found that wear volume loss increased as load increased for all sliding distances and some sliding speeds.For sliding speed of 220 mm/s and sliding distance of 1000 m,the wear volume losses under loads of 10,20,30,40 and 50 N were calculated to be 15.0,19.0,24.3,33.9 and 37.4 mm3,respectively.Worn surfaces show that abrasion and oxidation were present at a load of 10 N,which changes into delamination at a load of 50 N.ANOVA results show that the contributions of load,sliding distance and sliding speed were 12.99%,83.04%and 3.97%,respectively.The artificial neural networks(ANN),support vector regressor(SVR)and random forest(RF)methods were applied for the prediction of wear volume loss of AZ91 alloy.The correlation coefficient(R2)values of SVR,RF and ANN for the test were 0.9245,0.9800 and 0.9845,respectively.Thus,the ANN model has promising results for the prediction of wear performance of AZ91 alloy.

Exploration of the Impact Mechanism of Government Credibility Based on Variable Screening Method

Government credibility is an important asset of contemporary national governance, an important criterion for evaluating government legitimacy, and a key factor in measuring the effectiveness of government governance. In recent years, researchers’ research on government credibility has mostly focused on exploring theories and mechanisms, with little empirical research on this topic. This article intends to apply variable selection models in the field of social statistics to the issue of government credibility, in order to achieve empirical research on government credibility and explore its core influencing factors from a statistical perspective. Specifically, this article intends to use four regression-analysis-based methods and three random-forest-based methods to study the influencing factors of government credibility in various provinces in China, and compare the performance of these seven variable selection methods in different dimensions. The research results show that there are certain differences in simplicity, accuracy, and variable importance ranking among different variable selection methods, which present different importance in the study of government credibility issues. This study provides a methodological reference for variable selection models in the field of social science research, and also offers a multidimensional comparative perspective for analyzing the influencing factors of government credibility.

Modeling habitat suitability of range plant species using random forest method in arid mountainous rangelands

Mountainous rangelands play a pivotal role in providing forage resources for livestock, particularly in summer, and maintaining ecological balance. This study aimed to identify environmental variables affecting range plant species distribution, ecological analysis of the relationship between these variables and the distribution of plants, and to model and map the plant habitats suitability by the Random Forest Method(RFM) in rangelands of the Taftan Mountain, Sistan and Baluchestan Province, southeastern Iran. In order to determine the environmental variables and estimate the potential distribution of plant species, the presence points of plants were recorded by using systematic random sampling method(90 points of presence) and soils were sampled in 5 habitats by random method in 0–30 and 30–60 cm depths. The layers of environmental variables were prepared using the Kriging interpolation method and Geographic Information System facilities. The distribution of the plant habitats was finally modelled and mapped by the RFM. Continuous maps of the habitat suitability were converted to binary maps using Youden Index(?) in order to evaluate the accuracy of the RFM in estimation of the distribution of species potentialhabitat. Based on the values of the area under curve(AUC) statistics, accuracy of predictive models of all habitats was in good level. Investigating the agreement between the predicted map, generated by each model, and actual maps, generated from fieldmeasured data, of the plant habitats, was at a high level for all habitats, except for Amygdalus scoparia habitat. This study concluded that the RFM is a robust model to analyze the relationships between the distribution of plant species and environmental variables as well as to prepare potential distribution maps of plant habitats that are of higher priority for conservation on the local scale in arid mountainous rangelands.

Operational impacts to residual stands following ground-based skidding in Hyrcanian Forest, northern Iran

Hyrcanian （Caspian） Forest in northern Iran has a richness of biological diversity, with endemic and endangered species. The usage of ground-based skidding is well accepted practice for the extraction of timber from the forest, but this operation has tended to cause the greatest environmental problems. The aims of the study were to evaluate and comparison of operational impacts, residual stand damage, regeneration, and to quantify these effects such as： the extent of the damage, wounding patterns, size and distribution after logging operations that utilized two different methods： short log and long log. A Timbetjack cable skidder was used and the study location was in the Kheyrud Forest. Post harvesting assessment of damage to the residual stand was compared along skid trail by 100% inventory method and also for the assessment of regeneration damage along winching strips. The results show that along winching strips the percentage of damage to the regeneration was 44% and 36%, while the tree damages along skid trails reached 2.3% and 4.1% in the short log and long log methods, respectively. The greatest average amount of damage to a bole occurred along the first 1 m up from the ground （97%） and also within 4 m of the skidder centerline （80%）. These results show that the short log method causes less damage to the residual stand than the longog method. Tree location to skidder trail appears to have a significant effect on the number and height of scars on a tree. Well designed and constructed trails should be wide enough to allow wood extraction from the forest. Damage to the residual stand might be reduced by proper planning and training of logging crews.

A general multi-objective programming model for minimum ecological flow or water level of inland water bodies

Assessment of ecological flow or water level for water bodies is important for the protection of de- graded or degrading ecosystems caused by water shortage in arid regions, and it has become a key issue in water resources planning. In the past several decades, many methods have been proposed to assess ecological flow for rivers and ecological water level for lakes or wetlands. To balance water uses by human and ecosystems, we proposed a general multi-objective programming model to determine minimum ecological flow or water level for inland water bodies, where two objectives are water index for human and habitat index for ecosystems, respectively Using the weighted sum method for multi-objective optimization, minimum ecological flow or water level can be determined from the breakpoint in the water index-habitat index curve, which is similar to the slope method to de- termine minimum ecological flow from wetted perimeter-discharge curve. However, the general multi-objective programming model is superior to the slope method in its physical meaning and calculation method. This model provides a general analysis method for ecological water uses of different inland water bodies, and can be used to define minimum ecological flow or water level by choosing appropriate water and habitat indices. Several com- monly used flow or water level assessment methods were found to be special cases of the general model, including the wetted perimeter method and the multi-objective physical habitat simulation method for ecological river flow, the inundated forest width method for regeneration flow of floodplain forest and the lake surface area method for eco- logical lake level. These methods were applied to determine minimum ecological flow or water level for two repre- sentative rivers and a lake in northern Xinjiang of China, including minimum ecological flow for the Ertix River, minimum regeneration flow for floodplain forest along the midstream of Kaxgar River, and minimum ecological lake level for the Ebinur Lake. The results illustrated the versatility of the general model, and can provide references for water resources planning and ecosystem protection for these rivers and lake.

Using modified Soil Conservation Service curve number method to simulate the role of forest in flood control in the upper reach of the Tingjiang River in China

To improve flood control efficiency and increase urban resilience to flooding,the impacts of forest type change on flood control in the upper reach of the Tingjiang River(URTR) were evaluated by a modified model based on the Soil Conservation Service curve number(SCS-CN) method. Parameters of the model were selected and determined according to the comprehensive analysis of model evaluation indexes. The first simulation of forest reconstruction scenario,namely a coniferous forest covering 59.35km^2 is replaced by a broad-leaved forest showed no significant impact on the flood reduction in the URTR. The second simulation was added with 61.75km^2 bamboo forest replaced by broad-leaved forest,the reduction of flood peak discharge and flood volume could be improved significantly. Specifically,flood peak discharge of 10-year return period event was reduced to 7-year event,and the reduction rate of small flood was 21%-28%. Moreover,the flood volume was reduced by 9%-14% and 18%-35% for moderate floods and small floods,respectively. The resultssuggest that the bamboo forest reconstruction is an effective control solution for small to moderate flood in the URTR,the effect of forest conversion on flood volume is increasingly reduced as the rainfall amount increases to more extreme magnitude. Using a hydrological model with scenarios analysis is an effective simulation approach in investigating the relationship between forest type change and flood control. This method would provide reliable support for flood control and disaster mitigation in mountainous cities.

Determination of minimum flood flow for regeneration of floodplain forest from inundated forest width-stage curve

Floods are essential for the regeneration and growth of floodplain forests in arid and semiarid regions. However, river flows, and especially flood flows, have decreased greatly with the increase of water diversion from rivers and/or reservoir regulation, resulting in severe deterioration of floodplain ecosystems. Estimation of the flood stage that will inundate the floodplain forest is necessary for the forest＇s restoration or protection. To balance water use for economic purposes and floodplain forest protection, the inundated forest width method is proposed for estimating the minimum flood stage for floodplain forests from the inundated forest width-stage curve. The minimum flood stage is defined as the breakpoint of the inundated forest width-stage curve, and is determined directly or analytically from the curve. For the analytical approach, the problem under consideration is described by a multi-objective optimization model, which can be solved by the ideal point method. Then, the flood flow at the minimum flood stage （minimum flood flow）, which is useful for flow regulation, can be calculated from the stage-discharge curve. In order to protect the forest in a river floodplain in a semiarid area in Xinjiang subject to reservoir regulation upstream, the proposed method was used to determine the minimum flood stage and flow for the forest. Field survey of hydrology, topography, and forest distribution was carried out at typical cross sections in the floodplain. Based on the survey results, minimum flood flows for six typical cross sections were estimated to be between 306 m3/s and 393 m3/s. Their maximum, 393 m3/s, was considered the minimum flood flow for the study river reach. This provides an appropriate flood flow for the protection of floodplain forest and can be used in the regulation of the upstream reservoir.

Empirical Analysis of Forest Pest Control Efficiency from 2003 to 2014 in China

Three indexes including forest pest occurrence area,control area and input fund of 31 provinces from 2003 to 2014 were selected from Forestry Statistical Yearbook,to establish dynamic interaction index evaluation system with clustering robust regression model and Stata 13. 0 software. Total forest pest control efficiency in China was determined according to the computing result of entropy method. Suggestions such as improving forest pest control efficiency,increasing service efficiency and input amount of forest pest control input funds were put forward. It will provide empirical basis for target management evaluation of forest pest control work and accountability system.

A Framework on Fast Mapping of Urban Flood Based on a Multi-Objective Random Forest Model

Fast and accurate prediction of urban flood is of considerable practical importance to mitigate the effects of frequent flood disasters in advance.To improve urban flood prediction efficiency and accuracy,we proposed a framework for fast mapping of urban flood:a coupled model based on physical mechanisms was first constructed,a rainfall-inundation database was generated,and a hybrid flood mapping model was finally proposed using the multi-objective random forest(MORF)method.The results show that the coupled model had good reliability in modelling urban flood,and 48 rainfall-inundation scenarios were then specified.The proposed hybrid MORF model in the framework also demonstrated good performance in predicting inundated depth under the observed and scenario rainfall events.The spatial inundated depths predicted by the MORF model were close to those of the coupled model,with differences typically less than 0.1 m and an average correlation coefficient reaching 0.951.The MORF model,however,achieved a computational speed of 200 times faster than the coupled model.The overall prediction performance of the MORF model was also better than that of the k-nearest neighbor model.Our research provides a novel approach to rapid urban flood mapping and flood early warning.

Resilience-Driven Road Network Retrofit Optimization Subject to Tropical Cyclones Induced Roadside Tree Blowdown

This article focuses on decision making for retrofit investment of road networks in order to alleviate severe consequences of roadside tree blowdown during tropical cyclones.The consequences include both the physical damage associated with roadside trees and the functional degradation associated with road networks.A trilevel,two-stage,and multiobjective stochastic mathematical model was developed to dispatch limited resources to retrofit the roadside trees of a road network.In the model,a new metric was designed to evaluate the performance of a road network;resilience was considered from robustness and recovery efficiency of a road network.The proposed model is at least a nondeterministic polynomialtime hardness(NP-hard)problem,which is unlikely to be solved by a polynomial time algorithm.Pareto-optimal solutions for this problem can be obtained by a proposed trilevel algorithm.The random forest method was employed to transform the trilevel algorithm into a singlelevel algorithm in order to decrease the computation burden.Roadside tree retrofit of a provincial highway network on Hainan Island,China was selected as a case area because it suffers severely from tropical cyclones every year,where there is an urgency to upgrade roadside trees against tropical cyclones.We found that roadside tree retrofit investment significantly alleviates the expected economic losses of roadside tree blowdown,at the same time that it promotes robustness and expected recovery efficiency of the road network.

The phytochemical components of walnuts and their application for geographical origin based on chemical markers

Place of origin has an important influence on walnut quality and commercial value,which results in the requirement of rapid geographical traceability method.Thus,a method for geographical origin identification of walnuts on the basis of nutritional quality of walnuts from China was conducted.The concentrations of 43 phytochemical components were analyzed in walnut samples from five different walnut-producing regions of China.Based on 14 chemical markers selected by the Random Forest method from these phytochemical components,a new discriminant model for geographical origin was built,with the corresponding correct classification rate of 99.3%.In addition,the quantitative quality differences of walnuts from five regions were analyzed,with values of 0.17–1.43.Moreover,the top three chemical markers for the geographical origin discriminant analysis were Mo,V,and stearic acid,with contribution rates of 26.8%,18.9%,and 10.9%,respectively.This study provides a potentially viable method for application in food authentication.