基于工程设计图档的管理系统优化模型方法

针对工程设计图档管理系统的特点，从图档关系模型、版本控制、图像压缩和模糊检索等几个关键环节提出了优化的模型方法，节省存储空间和加快智能化检索速度，在实际应用中取得了很好的效果。

浅谈公路工程项目管理的优化方法

公路工程项目管理是一项系统性工作,由于其内容复杂且流程烦琐,为了保证项目管理质量,就需要利用信息模型优化法来提高管理效率与质量。该文对公路工程项目管理进行分析,并将排队理论作为信息模型优化的核心,提出信息模型优化法。结果显示,利用排队模型可以通过多线程作业来提高公路工程项目管理效率与质量。该文对项目管理信息模型优化法进行分析,可以提高公路工程项目管理水平。

常规测井方法描述复杂含气砂岩储层特征参数研究

通过对高孔低渗、低孔低渗等特征含气砂岩的储层岩性、物性对测井响应的不同的特点分析,建立了一套相应的储层参数测井评价方法。这些测井评价方法包括对于高孔低渗储层评价其孔隙性、含油性的库克法;对于低孔、低渗储层建立的测井非相关优化法;储层测井特征值参数权值法等方法。对于不同储层特征,用相应的储层测井评价方法,可有效地得到储层参数。计算结果、岩心分析数据与试气结论吻合,证明所建立的储层测井评价方法是合适的,为类似复杂储层参数研究提供了新思路,具有一定的参考价值。

模型优化法在滑坡变形分析中的应用

该文以文献〔1〕为基础 ,将初选出的最佳变形模型的模型参数作为带有动态噪声的状态向量 ,用卡尔曼滤波法进行滤波 ,并以此为基础建立滑坡变形预测模型。实例计算表明 。

Combining the genetic algorithms with artificial neural networks for optimization of board allocating

This paper introduced the Genetic Algorithms (GAs) and Artificial Neural Networks (ANNs), which have been widely used in optimization of allocating. The combination way of the two optimizing algorithms was used in board allocating of furniture production. In the experiment, the rectangular flake board of 3650 mm 1850 mm was used as raw material to allocate 100 sets of Table Bucked. The utilizing rate of the board reached 94.14 % and the calculating time was only 35 s. The experiment result proofed that the method by using the GA for optimizing the weights of the ANN can raise the utilizing rate of the board and can shorten the time of the design. At the same time, this method can simultaneously searched in many directions, thus greatly in-creasing the probability of finding a global optimum.

开关磁阻电机改进型简化磁链无位置传感器技术

针对简化磁链方法只能实现单相轮流导通,不利于电机出力的问题,提出一种基于特征位置磁链的改进型简化磁链开关磁阻电机位置估计方法。根据电感、转子位置、磁链三者之间的关系,以电感曲线的交点为特征位置,用实时计算得到的磁链与特征位置磁链比较获取转子位置信号。为更进一步简化位置估计算法,提出一种五点法磁链优化模型来自动生成特征位置磁链方法,并通过理论仿真分析,对五点法磁链模型进行了优化设计,该方法省去了实测磁链和创建磁链数据表的繁琐过程。实验结果验证了该方法的正确性和可行性。

Review of optimized layout of electric vehicle charging infrastructures

Electric vehicle is a kind of new energy vehicle which uses batteries as energy supply unit.A huge gap in charging infrastructures will be created by the expansion of electric vehicles.The effectiveness and rationality of charging facilities will directly affect the convenience and economy of the users,as well as the safe operation of the power grid.Three types of charging facilities:charging pile,charging station and battery swap station are introduced in this paper.According to the different methods of charging infrastructure planning,the research status of the method of determining charging demand points is expounded.And the spatial distribution of charging demand points extracted by the current site selection method has a certain deviation.Then the models and algorithms of charging infrastructure optimized layout are reviewed.Currently,many researches focus on three categories optimization objectives:benefit of power company side,investment cost of charging facility and user side cost,and the genetic algorithm and particle swarm optimization are the main solving algorithms.Finally,the relative methods and development trend of the charging infrastructures optimized layout are summarized,and some suggestions on the optimized layout of electric vehicle charging infrastructures are given forward.

A New Empirical Large Signal Model of 4H-SiC MESFETs for the Nonlinear Analysis

A new comprehensive empirical large signal model for 4H-SiC MESFETs is proposed. An enhanced drain current model,along with an improved charge conservation capacitance model,is presented by the improvement of the channel length modulation and the hyperbolic tangent function coefficient based on the Materka model. The Levenberg-Marquardt method is used to optimize the parameter extraction. A comparison of simulation resuits with experimental data is made,and good agreements of I-V curves, Pout （output power）, PAE （power added efficiency） ,and gain at the bias of Vos = 20V, Ips = 80mA as well as the operational frequency of 1.8GHz are obtained.

Modeling and Optimization for Short-term Scheduling of Multipurpose Batch Plants

In the past two decades, short-term scheduling of multipurpose batch plants has received significant attention. Most scheduling problems are modeled using either state-task-network or resource-task-network(RTN) process representation. In this paper, an improved mixed integer linear programming model for short-term schedul-ing of multipurpose batch plants under maximization of profit is proposed based on RTN representation and unit-specific events. To solve the model, a hybrid algorithm based on line-up competition algorithm and linear programming is presented. The proposed model and hybrid algorithm are applied to two benchmark examples in literature. The simulation results show that the proposed model and hybrid algorithm are effective for short-term scheduling of multipurpose batch plants.

Galerkin solution of Winkler foundation-based irregular Kirchhoff plate model and its application in crown pillar optimization

Irregular plates are very common structures in engineering,such as ore structures in mining.In this work,the Galerkin solution to the problem of a Kirchhoff plate lying on the Winkler foundation with two edges simply supported and the other two clamped supported is derived.Coordinate transformation technique is used during the solving process so that the solution is suitable to irregular shaped plates.The mechanical model and the solution proposed are then used to model the crown pillars between two adjacent levels in Sanshandao gold mine,which uses backfill method for mining operation.After that,an objective function,which takes security,economic profits and filling effect into consideration,is built to evaluate design proposals.Thickness optimizations for crown pillars are finally conducted in both conditions that the vertical stiffness of the foundation is known and unknown.The procedure presented in the work provides the guidance in thickness designing of complex shaped crown pillars and the preparation of backfill materials,thus to achieve the best balance between security and profits.

A new algorithm for stope boundary optimization

Stopes can be simply defined as an underground opening from which ore has been excavated.Selection of the best combination of available stope boundary will directly affect the profitability of the operation.While a few attempts has been initiated to generate the optimum stope boundary for underground mining, they fail to guarantee a true optimality in three-dimension block models.This paper proposed a new methodology which can find optimum stope layout for a given resource model in three-dimensions.The paper initially critically reviewed important stope boundary optimisation studies thus far, then proposed a new methodology in order to find the best stope layout for a given deposit.Subsequently it applied the proposed methodology into a block model to test its ability of producing optimum results and demonstrated its applicability in a number of different scenarios.In the last section, further analysis on strategies to find the optimum stope boundaries were demonstrated.The results prove that the proposed algorithm can find optimum stope boundaries and layouts in three-dimension for different stope sizes and stope selections trategies.

Multidisciplinary design optimization for air-condition production system based on multi-agent technique

In order to guarantee the overall production performance of the multiple departments in an air-condition production industry, multidisciplinary design optimization model for production system is established based on the multi-agent technology. Local operation models for departments of plan, marketing, sales, purchasing, as well as production and warehouse are formulated into individual agents, and their respective local objectives are collectively formulated into a multi-objective optimization problem. Considering the coupling effects among the correlated agents, the optimization process is carried out based on self-adaptive chaos immune optimization algorithm with mutative scale. The numerical results indicate that the proposed multi-agent optimization model truly reflects the actual situations of the air-condition production system. The proposed multi-agent based multidisciplinary design optimization method can help companies enhance their income ratio and profit by about 33% and 36%, respectively, and reduce the total cost by about 1.8%.

Multidisciplinary design optimization on production scale of underground metal mine

In order to ensure overall optimization of the underground metal mine production scale, multidisciplinary design optimization model of production scale which covers the subsystem objective function of income of production, safety and environmental impact in the underground metal mine was established by using multidisciplinary design optimization method. The coupling effects from various disciplines were fully considered, and adaptive mutative scale chaos immunization optimization algorithm was adopted to solve multidisciplinary design optimization model of underground metal mine production scale. Practical results show that multidisciplinary design optimization on production scale of an underground lead and zinc mine reflect the actual operating conditions more realistically, the production scale is about 1.25 Mt/a (Lead and zinc metal content of 160 000 t/a), the economic life is approximately 14 a, corresponding coefficient of production profits can be increased to 15.13%, safety factor can be increased to 5.4% and environmental impact coefficient can be reduced by 9.52%.

杠杆收购的融资探讨

企业并购离不开巨额资金的支持,单靠企业的自有资金难于支撑庞大的并购计划,因此,企业并购活动必然面临资金运作以及资金运作不当引起的财务风险.

Multi-objective coordination optimal model for new power intelligence center based on hybrid algorithm

In order to resolve the coordination and optimization of the power network planning effectively, on the basis of introducing the concept of power intelligence center (PIC), the key factor power flow, line investment and load that impact generation sector, transmission sector and dispatching center in PIC were analyzed and a multi-objective coordination optimal model for new power intelligence center (NPIC) was established. To ensure the reliability and coordination of power grid and reduce investment cost, two aspects were optimized. The evolutionary algorithm was introduced to solve optimal power flow problem and the fitness function was improved to ensure the minimum cost of power generation. The gray particle swarm optimization (GPSO) algorithm was used to forecast load accurately, which can ensure the network with high reliability. On this basis, the multi-objective coordination optimal model which was more practical and in line with the need of the electricity market was proposed, then the coordination model was effectively solved through the improved particle swarm optimization algorithm, and the corresponding algorithm was obtained. The optimization of IEEE30 node system shows that the evolutionary algorithm can effectively solve the problem of optimal power flow. The average load forecasting of GPSO is 26.97 MW, which has an error of 0.34 MW compared with the actual load. The algorithm has higher forecasting accuracy. The multi-objective coordination optimal model for NPIC can effectively process the coordination and optimization problem of power network.

Multi-objective optimization for leaching process using improved two-stage guide PSO algorithm

A mathematical mechanism model was proposed for the description and analysis of the heat-stirring-acid leaching process.The model is proved to be effective by experiment.Afterwards,the leaching problem was formulated as a constrained multi-objective optimization problem based on the mechanism model.A two-stage guide multi-objective particle swarm optimization(TSG-MOPSO) algorithm was proposed to solve this optimization problem,which can accelerate the convergence and guarantee the diversity of pareto-optimal front set as well.Computational experiment was conducted to compare the solution by the proposed algorithm with SIGMA-MOPSO by solving the model and with the manual solution in practice.The results indicate that the proposed algorithm shows better performance than SIGMA-MOPSO,and can improve the current manual solutions significantly.The improvements of production time and economic benefit compared with manual solutions are 10.5% and 7.3%,respectively.

Evaluation and optimization of secondary water supply system renovation

Due to pollution in second water supply system (SWSS),nine renovation alternative plans were proposed and com-prehensive evaluations of different plan based on Analytical Hierarchy Process (AHP) were presented in this paper. Comparisons of advantages and disadvantages among the plans of SWSS renovations provided solid foundation for selecting the most appro-priate plan for engineering projects. In addition,a mathematical model of the optimal combination of renovation plans has been set up and software Lingo was used to solve the model. As a case study,the paper analyzed 15 buildings in Tianjin City. After simulation of the SWSS renovation system,an optimal scheme was obtained,the result of which indicates that 10 out of those 15 buildings need be renovated in priority. The renovation plans selected for each building are the ones ranked higher in the com-prehensive analysis. The analysis revealed that the optimal scheme,compared with two other randomly calculated ones,increased the percentage of service population by 19.6% and 13.6% respectively,which significantly improved social and economical benefits.

Improvements in seismic event locations in a deep western U.S. coal mine using tomographic velocity models and an evolutionary search algorithm

Methods of improving seismic event locations were investigated as part of a research study aimed at reducing ground control safety hazards. Seismic event waveforms collected with a 23-station three-dimensional sensor array during longwall coal mining provide the data set used in the analyses. A spatially variable seismic velocity model is constructed using seismic event sources in a passive tomographic method. The resulting three-dimensional velocity model is used to relocate seismic event positions. An evolutionary optimization algorithm is implemented and used in both the velocity model development and in seeking improved event location solutions. Results obtained using the different velocity models are compared. The combination of the tomographic velocity model development and evolutionary search algorithm provides improvement to the event locations.

Modeling and Multi-objective Optimization of Refinery Hydrogen Network

The demand of hydrogen in oil refinery is increasing as market forces and environmental legislation, so hydrogen network management is becoming increasingly important in refineries. Most studies focused on single-objective optimization problem for the hydrogen network, but few account for the multi-objective optimization problem. This paper presents a novel approach for modeling and multi-objective optimization for hydrogen network in refineries. An improved multi-objective optimization model is proposed based on the concept of superstructure. The optimization includes minimization of operating cost and minimization of investment cost of equipment. The proposed methodology for the multi-objective optimization of hydrogen network takes into account flow rate constraints, pressure constraints, purity constraints, impurity constraints, payback period, etc. The method considers all the feasible connections and subjects this to mixed-integer nonlinear programming （MINLP）. A deterministic optimization method is applied to solve this multi-objective optimization problem. Finally, a real case study is intro-duced to illustrate the applicability of the approach.

Digital Model of Human Lower Extremity Musculoskeletal System Based on CT & MRI

A new method to reconstruct a comparatively complete muscle model of the human lower limb from CT and MRI data is presented. Topological structure of more than fourteen muscles is built and coordinates of origin and insertion points are given. Based on this model, straight-line model and centroid-line muscle model are acquired. Muscle force prediction is discussed according to the model reconstructed, and a multi-objective optimization method is put forward for evaluating muscle forces of the human lower extremity.