Integrating Variable Reduction Strategy With Evolutionary Algorithms for Solving Nonlinear Equations Systems

Nonlinear equations systems (NESs) are widely used in real-world problems and they are difficult to solve due to their nonlinearity and multiple roots. Evolutionary algorithms (EAs) are one of the methods for solving NESs, given their global search capabilities and ability to locate multiple roots of a NES simultaneously within one run. Currently, the majority of research on using EAs to solve NESs focuses on transformation techniques and improving the performance of the used EAs. By contrast, problem domain knowledge of NESs is investigated in this study, where we propose the incorporation of a variable reduction strategy (VRS) into EAs to solve NESs. The VRS makes full use of the systems of expressing a NES and uses some variables (i.e., core variable) to represent other variables (i.e., reduced variables) through variable relationships that exist in the equation systems. It enables the reduction of partial variables and equations and shrinks the decision space, thereby reducing the complexity of the problem and improving the search efficiency of the EAs. To test the effectiveness of VRS in dealing with NESs, this paper mainly integrates the VRS into two existing state-of-the-art EA methods (i.e., MONES and DR-JADE) according to the integration framework of the VRS and EA, respectively. Experimental results show that, with the assistance of the VRS, the EA methods can produce better results than the original methods and other compared methods. Furthermore, extensive experiments regarding the influence of different reduction schemes and EAs substantiate that a better EA for solving a NES with more reduced variables tends to provide better performance.      

Specification uncertainty in modeling internet adoption: A developing city case analysis

Internet adoption fosters economic growth and development. Specifying policy control drivers is particularly relevant for developing countries. However, there is no consensus on the most relevant variables. We explored 33.6 million potential models to identify the most important determinants of household internet adoption using stochastic search variable selection and socioeconomic data from Medellín, Colombia. We found that monthly income, the head of household education and voting, and having a computer and cable television at home are the most relevant variables.     

Estimates of pollutant temporal and spatial variability in commercial buildings from the joint urban 2003 field experiments

In this paper, we report on the indoor concentrations from a suite of full-scale outdoor tracer-gas point releases conducted in the downtown area of Oklahoma City in 2003. A point release experiment consisted of releases of sulfur hexafluoride (SF₆) in multiple buildings and from different outdoor locations. From the measurements, we are able to estimate the concentration variations indoors for a building operating under “typical” operating conditions. The mean indoor spatial coefficients of variation are 30% to 45% from a daytime outdoor release are around 80% during an outdoor evening release. Having estimates of the spatial coefficient of variation provides stakeholders, including first responders, with the likely range of concentrations in the building when little is known about the building characteristics and operating behavior, such as developing urban-scale hazard and consequence analyses. We show differences in indoor measurements at different distances to the release points, floors of the building, and heating, ventilation, and air conditioning system (HVAC) operation. We also show estimates at different time resolutions. The statistics show that in the studied medium to large commercial buildings, spatial differences would result in peak indoor concentrations in certain parts of the buildings that may be substantially higher than the building average. To our knowledge, very few tracer gas measurements have been conducted in buildings of this scope, particularly with measurements on multiple floors and within a floor. The resulting estimates of spatial variability provide a unique opportunity for hazard assessment, and comparison to multi-zone models.     

东峡煤矿主煤流运输系统智能化集控设计

通过对东峡煤矿主煤流运输系统的改造,设计了一套智能化集控系统,采用变频驱动,并结合料流传感器,增设无线基站、本安网络摄像仪和语音扩播终端等设备,实现了带式输送机载荷分布的自动调节,提高了系统的可靠性和运行效率,实现了减员、节能、增效的目的。     

电子探针对磁铁矿中变价元素Fe的测试方法

充分利用岛津电子探针在硬件上的优势，采用全元素测试，即包括超轻元素氧在内的所有元素直接测试的思路对磁铁矿进行了测试，根据电价平衡原则计算出变价元素的含量，并使用状态分析的方法验证了FeO和Fe2O3含量的Lβ/Lα特点，得到了较为理想的测试结果。     

双PWM变频调速系统在矿井提升机中的应用

针对目前大部分矿井提升机仍采用转子串电阻调速方法造成能量浪费的现状,提出了一种双PWM变频调速方案:三相电压型PWM整流器采用电压、电流双闭环控制,其中电流环引入前馈解耦控制,并结合空间矢量脉宽调制(SVPWM)算法来提高直流电压利用率。仿真实验的结果表明,该双PWM变频调速系统控制精度高、动态响应快、抗扰能力强,能有效地实现矿井提升机的节能降耗。     

带式输送机驱动滚筒的有限元分析

针对带式输送机驱动滚筒轴向受力情况,提出了正态分布模型,结合ANSYS-APDL的语言编辑能力,用ANSYS Workbench对均匀分布、一阶正弦分布和正态分布的4种模型进行有限元分析,得到驱动滚筒应力应变图及位移变形的对比情况,为日后实验验证与优化设计提供理论支持。     

基于变权与正态云理论的煤矿安全评价及应用

为准确对煤矿安全状态作出客观评价,综合考虑评估过程中指标的模糊性和状态随机性,构建基于变权与正态云理论的煤矿安全状态评估模型。结合正态云的数字特征量期望、熵、超熵组成的特定结构函数确定安全状态评判矩阵,得出各评价指标隶属于不同等级的确定度。同时为了避免常权方法确定权重的局限性及突出关键指标对综合评判结果的影响,引入变权理论对常权权重进行处理得到变权。结合实例研究,发现基于变权云理论评判方法对取值较差的指标作用不会被其他指标作用中和,可以有效地反映煤矿的真实安全状态,能够为煤矿的安全风险预测提供了一种技术途径。     

Process monitoring method based on correlation variable classification and vine copula

Chemical processes are becoming increasingly complicated, leading to an increase in process variables and more complex relationships among them. The vine copula has a significant advantage in portraying the dependence of high-dimensional variables. However, as the dimensions increase, the vine copula model incurs a high computational load; such pressure greatly reduces model efficiency. Relationships among variables in the industrial process are complex. Different variables may be strongly or weakly associated or even independent. This paper proposes a process monitoring method based on correlation variable classification and vine copula. The weighted correlation measure is first used to divide variables into a correlated subspace and weakly correlated subspace. Then, two vine structures, C-vine and D-vine, are applied to the correlated and weakly correlated subspaces, respectively. This method takes advantage of C-vine for correlated variables and the flexibility of D-vine for weakly correlated variables. Finally, comprehensive statistics are established based on different subspaces. Monitoring results of the numerical system and the Tennessee Eastman process demonstrate the effectiveness and validity of the proposed method.     

变截面涡旋盘高速铣削仿真加工与实验研究

为减小变截面涡旋盘涡旋齿的变形,提高加工精度,需确定合理的铣削参数。开展了变截面涡旋盘高速铣削仿真与实验研究以确定铣削参数的合理取值范围;选用HT250变截面涡旋盘为研究对象,研究了更接近实际的材料本构模型、刀-屑摩擦模型和热传导控制方程等关键技术;建立了变截面涡旋盘几何模型和简化后的二维铣削模型,利用ABAQUS软件仿真切屑成形过程及不同的铣削参数对铣削力、铣削热影响的变化曲线;通过多因素正交实验加工变截面涡旋盘。结果表明:当主轴转速为3500 r/min、每齿进给量为0.1 mm以及切削深度为2.5 mm时进行铣削更加合理。铣削变截面涡旋盘的研究为加工参数的选择提供了依据和参考;依据实验后所得的铣削参数进行铣削可减小铣削力、铣削温度及齿变形,提高了变截面涡旋盘的加工效率和质量。