Optimization of Open-cast Mining Procedure Based on RSR Method

To explore the optimal evaluation mechanism of open-cast mining procedure,this paper takes the actual operation status of Huolinhe No.1 Open-cast Mine as the research basis,and makes a deep analysis of the four representative mining procedures proposed by this mine.A detailed and comprehensive evaluation system is constructed using rank-sum ratio(RSR)method.The system covers 17 key indicators and aims to evaluate the advantages and disadvantages of each scheme in an all-round and multi-angle manner.Through the calculation and analysis by RSR method,the comprehensive evaluation of the four types of mining procedure schemes is carried out,and finally the secondary river improvement project is determined as the optimal mining implementation scheme,and the joint mining scheme of the south and north areas is the alternative strategy.The research results of this paper are objective,clear and definite,can not only reveal the effectiveness and feasibility of RSR method in solving the problem of open-cast mining procedure optimization,but also provide a strong technical support and decision-making basis for the future production development of Huolinhe No.1 Open-cast Mine.Thus,this study is expected to further promote the scientific and refined process of mining operations.

Mixture Optimization by the CARSO Procedure and DCM Strategies

The paper illustrates a new way of using the CARSO procedure for response surfaces analyses derived from innovative experimental designs in multivariate spaces, based on Double Circulant Matrices (DCMs). We report a case study regarding a design based on a DCM for 4 variables. The final response surface model is obtained by the formerly developed CARSO method.

The CARSO (Computer Aided Response Surface Optimization) Procedure in Optimization Studies

The paper illustrates innovative ways of using the CARSO (Computer Aided Response Surface Optimization) procedure for response surfaces analyses derived by DCM4 experimental designs in multivariate spaces. Within this method, we show a new feature for optimization studies: the results of comparing their quadratic and linear models for discussing the best way to compute the most reliable predictions of future compounds.

Optimization of Pulsed-field Gel Electrophoresis Procedure for Bacillus cereus

In order to develop a rapid and reliable method for B. cereus genotyping, factors influencing PFGE results, including preparation of bacterial cells embedded in agarose, lysis of embedded cells, enzymatic digestion of intact genomic DNA, and electrophoresis parameters allowing for reproducible and meaningful DNA fragment separation, were controlled. Optimal cellular growth （Luria-Bertani agar plates for 12-18 h） and lysis conditions （4 h incubation with 500 μg/mL lysozyme） produced sharp bands on the gel.

Research on the Operation Mechanism of Claim in Civil Procedure Law and the Applications on Court Trial Way Reform

In this paper, we conduct research on the operation mechanism of claim in civil procedure law and the applications on the court trial way reform. The ultimate goal of the rule of law lies in identifying and protecting the rights of citizens. Way to protect the rights of citizens is diverse, but the judicial relief is the most basic and important form of insurance. Everyone can “into” the court and get the impartiality of the judicial relief, is a measure of a country judicial level height and the rule of law implementation degree of important yardstick. Judicial system and judicial procedure to build and build a better, if the subject of litigation rights are not being met and the safeguard, can’t get through the door and it is the legislators and legal scholars over the many efforts are meaningless, under this basic condition, we propose the new perspective on the corresponding issues that is necessary.

Multi-Objective Optimization of the Ultrasonic Scalpel Rod and Tip with Improved Performance:Vibration Frequency,Amplitude,and Service Life

Ultrasonic scalpel design for minimally invasive surgical procedures is mainly focused on optimizing cutting performance.However,an important issue is the low fatigue life of traditional ultrasonic scalpels,which affects their long-term reliability and effectiveness and creates hidden dangers for surgery.In this study,a multi-objective optimal design for the cutting performance and fatigue life of ultrasonic scalpels was proposed using finite element analysis and fatigue simulation.The optimal design parameters of resonance frequency and amplitude were determined.By setting the transition fillet and keeping the gain structure away from the node position to enable the scalpel to have a high service life with excellent cutting performance.The frequency modulation method of setting the vibration node bosses at the node position and setting the vibration antinode grooves at the antinode position was compared.Then,the mechanism of the influence of various design elements,such as tip,shank,node position,and antinode position,on the resonance frequency,amplitude,and fatigue life of the ultrasonic scalpel was analyzed,and the optimal design principles of the ultrasonic scalpel were obtained.The proposed ultrasonic scalpel design was confirmed by simulations,impedance measurements,and liver tissue cutting experiments,demonstrating its feasibility and enhanced performance.This research introduces innovative design strategies to improve the fatigue life and performance of ultrasonic scalpels to address an important issue in minimally invasive surgery.

Method for secondary spring load equalization of railway vehicles with two-stage spring suspension: Modeling and optimal regulation

To ensure running safety,the secondary spring loads of railway vehicles must be well equalized.Due to the coupling interactive effects of these hyper static suspended structures,the equalization adjustment through shimming procedure is quite complex.Therefore,an effective and reliable method in application is developed in this paper.Firstly,the best regulation of spring load is solved based on a mechanical model of the secondary suspension system,providing a target for actual adjustment.To reveal the relationship between secondary spring load distribution and shim quantity sequence,a forecasting model is constructed and then modified experimentally with consideration of car body’s elastic deformation.Further,a gradient-based algorithm with a momentum operation is proposed for the load optimization.Effectiveness of the whole method has been verified on a test rig.It is experimentally confirmed that this research provides an important basis for achieving an optimal regulation of spring load distribution for multiple types of railway vehicles.

A Particle Swarm Optimization Algorithm for a 2-D Irregular Strip Packing Problem

Two-Dimensional Irregular Strip Packing Problem is a classical cutting/packing problem. The problem is to assign, a set of 2-D irregular-shaped items to a rectangular sheet. The width of the sheet is fixed, while its length is extendable and has to be minimized. A sequence-based approach is developed and tested. The approach involves two phases;optimization phase and placement phase. The optimization phase searches for the packing sequence that would lead to an optimal (or best) solution when translated to an actual pattern through the placement phase. A Particle Swarm Optimization algorithm is applied in this optimization phase. Regarding the placement phase, a combined algorithm based on traditional placement methods is developed. Competitive results are obtained, where the best solutions are found to be better than, or at least equal to, the best known solutions for 10 out of 31 benchmark data sets. A Statistical Design of Experiments and a random generator of test problems are also used to characterize the performance of the entire algorithm.

Review: Recent Developments in the Uncertainty-Based Aero-Structural Design Optimization for Aerospace Vehicles

With the increasing demands of aircraft design,the traditional deterministic design can hardly meet the requirements of fine design optimization because uncertainties may exist throughout the whole lifecycle of the aircraft. To enhance the robustness and reliability of the aircraft design, Uncertainty Multidisciplinary Design Optimization( UM DO) has been developing for a long time. This paper presents a comprehensive reviewof UM DO methods for aerospace vehicles,including basic UM DO theory and research progress of its application in aerospace vehicle design. Firstly,the UM DO theory is preliminarily introduced,with giving the definition and classification of uncertainty as well as its sources corresponding to the aircraft design. Then following the UM DO solving process, the application in different coupled disciplines is separately discussed during the aircraft design process,specifically clarifying the UM DO methods for aerostructural optimization. Finally,the main challenges of UM DO and the future research trends are given.

Design of Vehicle Routing by Integrating Optimization and Simulated Annealing Approach

The vehicle routing problem (VRP) can be described as the problem of designing the optimal delivery or collection routes from one or several depots to a number of geographically scattered customers, subject to load constraints. The routing decision involves determining which of the demand s will be satisfied by each vehicle and what route each vehicle will follow in s erving its assigned demand in order to minimize total delivery cost. In this pap er, a methodology for the design of VRP by integrating optimization and simulate d annealing (SA) approach is presented hierarchically. To express the problem of vehicle routing, a new mathematical formulation is first conducted. The objecti ve function involves both the delivery cost and the vehicle acquisition cost wit h load constraints. A heuristic is then proposed to solve this problem by using SA procedure in conjunction with any solution procedure of travelling salesman p roblem (TSP). The initial configuration is arranged as one vehicle route ser ving one customer. The SA searching procedure is then developed to combine custo mer to any one of the vehicle routes existed in the system if the capacity and c ost are attractive. An important concept of this proposed heuristic is that it attempts to minimize total number of vehicle required in the system on the b asis of the fixed cost and the variable cost view points. In addition, this appr oach can be easily adapted to accommodate many additional problem complexities.

Optimization of Map Compilation for County-level Land Consolidation Planning

Based on practice of the land consolidation planning in Changfeng County of Hefei City,taking full account of reality of land consolidation and its significance as livelihood project,we analyzed map compilation procedure.In combination with actual effect of land consolidation,we carried out consolidation assessment of same elements by overall planning method,and optimized the map compilation for county-level land consolidation planning.Results show that planning map of land consolidation potential is to be improved and legends should be merged.After consolidation of legends,it is convenient to apply in potential planning map and solve complicated problem of reading maps.

Mauro: A Novel Strategy for Optimizing Mixture Properties

The paper illustrates an innovative procedure for experimental design in mixture analysis. It relies on D-optimal designs performed on the combinatorial explosion of five levels of components composition, keeping in mind the requirements of Central Composite Designs. The final response surface model is obtained by the formerly developed CARSO method.

Experimental Design for Optimizing a Mixture of Materials plus an Evaporating Solvent

The paper illustrates a further new way of using the CARSO procedure for response surfaces analyses derived from experimental designs based on Double Circulant Matrices (DCMs). We report a case study regarding a design based on a mixture of three chemicals plus an evaporating solvent, in order to compare the relative reliability of designs based either on 3 only or on all 4 factors. We show that both designs give the same results, but the second is preferable because it represents the real situation at the beginning of the process, so that it is possible to know the required amount of solvent that should be used for each experiment. Obviously this applies to any number of factors using the correspondent DCM.

A Gauss-Newton Approach for Nonlinear Optimal Control Problem with Model-Reality Differences

Output measurement for nonlinear optimal control problems is an interesting issue. Because the structure of the real plant is complex, the output channel could give a significant response corresponding to the real plant. In this paper, a least squares scheme, which is based on the Gauss-Newton algorithm, is proposed. The aim is to approximate the output that is measured from the real plant. In doing so, an appropriate output measurement from the model used is suggested. During the computation procedure, the control trajectory is updated iteratively by using the Gauss-Newton recursion scheme. Consequently, the output residual between the original output and the suggested output is minimized. Here, the linear model-based optimal control model is considered, so as the optimal control law is constructed. By feed backing the updated control trajectory into the dynamic system, the iterative solution of the model used could approximate to the correct optimal solution of the original optimal control problem, in spite of model-reality differences. For illustration, current converted and isothermal reaction rector problems are studied and the results are demonstrated. In conclusion, the efficiency of the approach proposed is highly presented.

Maintaining an Optimal Flow of Forest Products under a Carbon Market: Approximating a Pareto Set of Optimal Silvicultural Regimes for Eucalyptus fastigata

A competitive co-evolutionary Multi-Objective Genetic Algorithm (cc-MOGA) was used to approximate a Pareto front of efficient silvicultural regimes for Eucalyptus fastigata. The three objectives to be maximised included, sawlog, pulpwood and carbon sequestration payment. Three carbon price scenarios (3CPS), i.e. NZ $25, NZ $50 and NZ $100 for a tonne of CO2 sequestered, were used to assess the impact on silvicultural regimes, against a fourth non-carbon Pareto set of efficient regimes (nonCPS), determined from a cc-MOGA with two objectives, i.e. competing sawlog and pulpwood productions. Carbon prices included in stand valuation were found to influence the silvicultural regimes by increasing the rotation length and lowering the final crop number before clearfell. However, there were no significant changes in the frequency, timing, and intensity of thinning operations amongst all the four Pareto sets of solutions. However, the 3CPS were not significantly different from each other, which meant that these silvicultural regimes were insensitive to the price of carbon. This was because maximising carbon sequestration was directly related to the biological growth rate. As such an optimal mix of frequency, intensity, and timing of thinning maintained maximum growth rate for as long as possible for any one rotation.

Simplex Optimization and Its Applicability for Solving Analytical Problems

Formulation of the simplex matrix referred to n-D space, is presented in terms of the scalar product of vectors, known from elementary algebra. The principles of a simplex optimization procedure are presented on a simple example, with use of a target function taken as a criterion of optimization, where accuracy and precision are treated equally in searching optimal conditions of a gravimetric analysis.

地方立法程序优化问题研究

地方立法机关按照法定权限和法定程序制定地方性法规,地方立法程序在地方法治建设中发挥着关键性的作用。科学立法构成地方立法程序的合理性指导,民主立法构成地方立法程序的正当性来源,依法立法构成地方立法程序的合法性要求。地方立法程序一般由地方立法的一般程序、设区的市的地方立法程序、区域协同立法的程序和“快速立法”的程序等构成。地方立法程序优化的基本内涵包括坚持以人民为中心的全过程人民民主立法,全面贯彻新发展理念的地方立法,以行政问责方式纠错的地方性法规,以及变通规定和补充规定的地方性法规等。实现地方立法程序优化可以通过地方基层立法体系的结构性优化,实现地方行政规范的现代化,加强地方立法协商吸纳民意民智和加强党对地方立法的全方位领导等途径,深入推进地方的科学立法、民主立法和依法立法。

基于周期特征提取的DLnet预测模型研究

现有的预测方法很少独立分析能源消耗的周期性特征。本文提出了一个短期办公建筑能耗预测模型(DLnet),以解决周期性能耗数据利用效率低下的问题。首先,利用STL对能耗数据的周期成分进行分解,通过网格搜索算法寻找能耗数据的最优周期;然后,根据最优周期构建周期块;再根据周期块的数据形状构建时间序列块数据;之后,利用长短期记忆(LSTM)对时间序列块数据和周期块数据进行训练和学习;最后,通过线性回归将时间序列块数据和周期块数据的预测结果进行融合。事实证明,所提出的模型的4个预测精度指标分别比LSTM模型高7%,21%,25%和26%。

个人信息保护公益诉讼制度建构路径优化——基于实体法与程序法交互方法

个人信息保护公益诉讼兼具实体法与程序法双重属性,基于实体法或程序法单一维度的制度建构将会陷入“一元观”困境。实体法与程序法交互为个人信息保护公益诉讼程序建构提供一种实体法关照。通过优化最具交互特征的三个支点:受案范围、责任形式和证明责任,不仅能够促进个人信息保护公益诉讼制度建构的二元论,也有利于推动实体法与程序法的一体化衔接,实现司法程序正义与实质正义。其一,从实体法维度,将“不特定多数人”公共利益说作为基础,增加“规模性”与“无差别性”的标准,解决受案范围“众多个人权益”的程序判断难题。其二,从程序法维度,通过诉讼信托的方式,允许原告受让惩罚性赔偿请求权,解决惩罚性赔偿这一责任形式缺乏实体适用空间难题。其三,从交互维度,一方面承认法官裁量分配证明责任,解决“规范说”在新型复杂案件的实体失范难题;另一方面设定证明责任减轻的请求权基础,解决裁判失度的程序适用难题。

高比例光伏接入的配电网分布式运行优化技术

高渗透率光伏和储能并网的现代配电网具有规模庞大、设备众多、运行工况复杂多变的特点,传统的集中式优化方法不再适用。与此同时,有载调压变压器、并联电容器等均为传统离散设备,导致配电网有功无功功率协调优化模型呈现非凸特性,而当前通用分布式算法仅适用于求解凸模型。为解决该问题,提出了计及模型非凸特性的配电网分布式有功无功功率协调优化方法。以提高配电网运行经济性为目标,利用随机规划理论进行光伏有功功率不确定性刻画,建立配电网分布式随机有功无功功率协调优化模型。针对所建模型的非凸特性提出基于交替寻优过程的分布式算法,实现该模型可靠求解。最后通过PG&E69节点系统进行算例分析,验证了所提分布式有功无功功率协调优化方法的有效性以及分布式算法的可靠性。