PLC梯形图输出元件网络设计法探讨

PLC是当今电气自动化领域中不可替代的中心控制器件,它的广泛应用在一定程度上取决于应用程序的开发和编制。为简便快速编制PLC应用程序,构思了一种输出元件网络设计法。由于此设计法能简便快捷地完成大多数PLC控制程序的编制,因此在PLC应用程序的开发和编制方面具有一定的使用价值。在对这种方法进行简单介绍的基础上,结合一个实例对其编制的关键步骤进行了探讨。

Dimension-down iterative algorithm for the mixed transportation network design problem

An optimal dimension-down iterative algorithm （DDIA） is proposed for solving a mixed （continuous/ discrete） transportation network design problem （MNDP）, which is generally expressed as a mathematical programming with equilibrium constraints （MPEC）. The upper level of the MNDP aims to optimize the network performance via both the expansion of existing links and the addition of new candidate links, whereas the lower level is a traditional Wardrop user equilibrium （UE） model. The idea of the proposed DDIA is to reduce the dimensions of the problem. A group of variables （discrete/continuous） are fixed to altemately optimize another group of variables （continuous/discrete）. Some continuous network design problems （CNDPs） and discrete network design problems （DNDPs） are solved repeatedly until the optimal solution is obtained. A numerical example is given to demonstrate the efficiency of the proposed algorithm.

Joint Network and Fountain Codes Design for RelayAssisted Multi-User System

In relay-assisted multi-user system, relay coding is important to enhance the robustness and reliability of cooperative transmission. For better adaptability and efficiency, two joint network and fountain coding(JNFC) schemes are proposed. When the condition of all direct channels is worse, JNFC scheme based on distributed LT(DLT) codes is used. Otherwise, JNFC scheme based on multi-dimensional LT(MD-LT) codes is suited. For both two above-mentioned schemes, the united degree distribution design method for short-length fountain codes is proposed. For the latter scheme, MD-LT codes are proposed for equal error protection(EEP) of each user. Simulation results and analysis show that the united degree distribution need less decoding overhead compared with other degree distribution for short-length fountain codes. And then, all users are protected equally in despite of asymmetric uplinks.

Design of heat exchanger network based on entransy theory

The heat exchanger network(HEN) synthesis problem based on entransy theory is analyzed. According to the characteristics of entransy representation of thermal potential energy, the entransy dissipation represents the irreversibility of the heat transfer process, the temperature difference determines the entransy dissipation, and four HEN design steps based on entransy theory are put forward. The present study shows how it is possible to set energy targets based on entransy and achieve them with a network of heat exchangers by an example of heat exchanger network design for four streams. In order to verify the correctness of the heat exchanger networks design method based on entransy theory, the synthesis of the HEN for the diesel hydrogenation unit is studied. Using the heat exchange networks design method based on entransy theory, the HEN obtained is consistent with energy targets. The entransy transfer efficiency of HEN based on entransy theory is 92.29%, higher than the entransy transfer efficiency of the maximum heat recovery network based on pinch technology.

Optimal operation of water supply systems with tanks based on genetic algorithm

In view of the poor water supply system’s network properties, the system’s complicated network hydraulic equations were replaced by macroscopic nodal pressure model and the model of relationship between supply flow and water source head. By using pump-station pressure head and initial tank water levels as decision variables, the model of optimal allocation of water supply between pump-sources was developed. Genetic algorithm was introduced to deal with the model of optimal allocation of water supply. Methods for handling each constraint condition were put forward, and overcome the shortcoming such as premature convergence of genetic algorithm; a solving method was brought forward in which genetic algorithm was combined with simulated annealing technology and self-adaptive crossover and mutation probabilities were adopted. An application example showed the feasibility of this algorithm.

A procedure for design of hydrogen networks with multiple contaminants

It is necessary to reduce hydrogen consumption to meet increasingly strict environmental and product-quality regulations for refinery plants. In this paper, the concentration potential concepts proposed for design of water-using networks are extended to synthesis of hydrogen networks with multiple contaminants. In the design procedure, the precedence of processes is determined by the values of concentration potential of demands.The usage of complementary source pair(s) to reduce utility consumption is investigated. Three case studies are presented to illustrate the effectiveness of the method. It is shown that the design procedure has clear engineering meaning.

Satellite Constellation Design with Multi-Objective Genetic Algorithm for Regional Terrestrial Satellite Network

Constellations design for regional terrestrial-satellite network can strengthen the coverage for incomplete terrestrial cellular network. In this paper, a regional satellite constellation design scheme with multiple feature points and multiple optimization indicators is proposed by comprehensively considering multi-objective optimization and genetic algorithm, and "the Belt and Road" model is presented in the way of dividing over 70 nations into three regular target areas. Following this, we formulate the optimization model and devise a multi-objective genetic algorithm suited for the regional area with the coverage rate under simulating, computing and determining. Meanwhile, the total number of satellites in the constellation is reduced by calculating the ratio of actual coverage of a single-orbit constellation and the area of targets. Moreover, the constellations' performances of the proposed scheme are investigated with the connection of C++ and Satellite Tool Kit(STK). Simulation results show that the designed satellite constellations can achieve a good coverage of the target areas.

Design and Implementation of Weibo Sentiment Analysis Based on LDA and Dependency Parsing

Information content security is a branch of cyberspace security. How to effectively manage and use Weibo comment information has become a research focus in the field of information content security. Three main tasks involved are emotion sentence identification and classification,emotion tendency classification,and emotion expression extraction. Combining with the latent Dirichlet allocation(LDA) model,a Gibbs sampling implementation for inference of our algorithm is presented,and can be used to categorize emotion tendency automatically with the computer. In accordance with the lower ratio of recall for emotion expression extraction in Weibo,use dependency parsing,divided into two categories with subject and object,summarized six kinds of dependency models from evaluating objects and emotion words,and proposed that a merge algorithm for evaluating objects can be accurately evaluated by participating in a public bakeoff and in the shared tasks among the best methods in the sub-task of emotion expression extraction,indicating the value of our method as not only innovative but practical.

Remanufacturing closed-loop supply chain network design based on genetic particle swarm optimization algorithm

As the huge computation and easily trapped local optimum in remanufacturing closed-loop supply chain network (RCSCN) design considered, a genetic particle swarm optimization algorithm was proposed. The total cost of closed-loop supply chain was selected as fitness function, and a unique and tidy coding mode was adopted in the proposed algorithm. Then, some mutation and crossover operators were introduced to achieve discrete optimization of RCSCN structure. The simulation results show that the proposed algorithm can gain global optimal solution with good convergent performance and rapidity. The computing speed is only 22.16 s, which is shorter than those of the other optimization algorithms.

Design and analysis of a network coding algorithm for ad hoc networks

Network coding is proved to have advantages in both wireline and wireless networks. Especially, appropriate network coding schemes are programmed for underlined networks. Considering the feature of strong node mobility in aviation communication networks, a hop-by-hop network coding algorithm based on ad hoc networks was proposed. Compared with COPE-like network coding algorithms, the proposed algorithm does not require overhearing from other nodes, which meets confidentiality requirements of aviation communication networks. Meanwhile, it does save resource consumption and promise less processing delay. To analyze the performance of the network coding algorithm in scalable networks with different traffic models, a typical network was built in a network simulator, through which receiving accuracy rate and receiving delay were both examined.The simulation results indicate that, by virtue of network coding, the proposed algorithm works well and improves performance significantly. More specifically, it has better performance in enhancing receiving accuracy rate and reducing receiving delay, as compared with any of the traditional networks without coding. It was applied to both symmetric and asymmetric traffic flows and, in particular, it achieves much better performance when the network scale becomes larger. Therefore, this algorithm has great potentials in large-scale multi-hop aviation communication networks.

An Ant Colony Algorithm Based on Cross-Layer Design for Routing and Wavelength Assignment in Optical Satellite Networks

This paper introduces an ant colony routing and wavelength assignment algorithm based on cross-layer design(CL-ACRWA),which can overcome the adverse effects of Doppler wavelength shift on data transmission in optical satellite networks. Firstly, a cross-layer optimization model is built, which considers the Doppler wavelength shift, the transmission delay as well as wavelength-continuity constraint. Then an ant colony algorithm is utilized to solve the cross-layer optimization model, resulting in finding an optimal light path satisfying the above constraints for every connection request. The performance of CL-ACRWA is measured by the communication success probability, the convergence property and the transmission delay. Simulation results show that CL-ACRWA performs well in communication success probability and has good global search ability as well as fast convergence speed. Meanwhile, the transmission delay can meet the basic requirement of real-time transmission of business.

HDNBS: An approach for search in decentralized and unstructured P2P

Decentralized and unstructured peer-to-peer applications such as Gnutella are attractive because they require no centralized directories and no precise control over network topology or data placement. Search algorithm is the major component of the distributed system and its efficiency also does influence the systems performance. However the flooding-based query algorithm used in Gnutella produces huge traffic and does not scale well. Gnutella-like P2P topology has power-law characteristic, so a search algorithm was proposed based on high degree nodes of power-law network, High Degree Nodes-Based Search （HDNBS）. Extensive simulation results show that this algorithm performs on power-law networks very well, achieves almost 100% success rates, produces O（logN） messages per query and can locate target file within O（lagN） hops.

Hybrid optimization model of product concepts

Deficiencies of applying the simple genetic algorithm to generate concepts were specified. Based on analyzing conceptual design and the morphological matrix of an excavator, the hybrid optimization model of generating its concepts was proposed, viz. an improved adaptive genetic algorithm was applied to explore the excavator concepts in the searching space of conceptual design, and a neural network was used to evaluate the fitness of the population. The optimization of generating concepts was finished through the ＂evolution - evaluation＂ iteration. The results show that by using the hybrid optimization model, not only the fitness evaluation and constraint conditions are well processed, but also the search precision and convergence speed of the optimization process are greatly improved. An example is presented to demonstrate the advantages of the orooosed method and associated algorithms.

A Brief Analysis of the Influence of Online Media on Fashion Design

The 21 st century is a time of digitization and infurmationization. Online media have been going forward rapidly and have penetrated into various aspects of people＇ s life, thus having a significant impact on people＇ s production and life. Under such circumstance, traditional fashion indnstry has also been influenced by online media and has gradually transformed to digitalization. Fashion design is likely to get away from simplex manual design and to transform to the design method of man-machine synergy. The introduction of network technique into fashion design will bring vast potential for future development of fashion design.

Times Series Prediction to Basis of a Neural Network Conceived by a Real Genetic Algorithm

Neural network and genetic algorithms are complementary technologies in the design of adaptive intelligent system. Neural network learns from scratch by adjusting the interconnections betweens layers. Genetic algorithms are a popular computing framework that uses principals from natural population genetics to evolve solutions to problems. Various forecasting methods have been developed on the basis of neural network, but accuracy has been matter of concern in these forecasts. In neural network methods forecasted values depend to the choose of neural predictor structure, the number of the input, the lag. To remedy to these problem, in this paper, the authors are investing the applicability of an automatic design of a neural predictor realized by real Genetic Algorithms to predict the future value of a time series. The prediction method is tested by using meteorology time series that are daily and weekly mean temperatures in Melbourne, Australia, 1980-1990.

Unit Commitment with Production Cost Uncertainty： A Recourse Programming Method

Many studies have considered the solution of Unit Commitment problems for the management of energy networks. In this field, earlier work addressed the problem in determinist cases and in cases dealing with demand uncertainties. In this paper, the authors develop a method to deal with uncertainties related to the cost function. Indeed, such uncertainties often occur in energy networks （waste incinerator with a priori unknown waste amounts, cogeneration plant with uncertainty of the sold electricity price...）. The corresponding optimization problems are large scale stochastic non-linear mixed integer problems. The developed solution method is a recourse based programming one. The main idea is to consider that amounts of energy to produce can be slightly adapted in real time, whereas the on/off statuses of units have to be decided very early in the management procedure. Results show that the proposed approach remains compatible with existing Unit Commitment programming methods and presents an obvious interest with reasonable computing loads.

DESIGN METHODOLOGY OF NETWORKED SOFTWARE EVOLUTION GROWTH BASED ON SOFTWARE PATTERNS

Recently, some new characteristics of complex networks attract the attentions of scientist, in different fields, and lead to many kinds of emerging research directions. So far, most of the researcl work has been limited in discovery of complex network characteristics by structure analysis in large-scale software systems. This paper presents the theoretical basis, design method, algorithms and experiment results of the research. It firstly emphasizes the significance of design method of evolution growth for network topology of Object Oriented （OO） software systems, and argues that the selection and modulation of network models with various topology characteristics will bring un-ignorable effect on the process, of design and implementation of OO software systems. Then we analyze the similar discipline of ＂negation of negation and compromise＂ between the evolution of network models with different topology characteristics and the development of software modelling methods. According to the analysis of the growth features of software patterns, we propose an object-oriented software network evolution growth method and its algorithms in succession. In addition, we also propose the parameter systems for OO software system metrics based on complex network theory. Based on these parameter systems, it can analyze the features of various nodes, links and local-world, modulate the network topology and guide the software metrics. All these can be helpful to the detailed design, implementation and performance analysis. Finally, we focus on the application of the evolution algorithms and demonstrate it by a case study. Comparing the results from our early experiments with methodologies in empirical software engineering, we believe that the proposed software engineering design method is a computational software engineering approach based on complex network theory. We argue that this method should be greatly beneficial for the design, implementation, modulation and metrics of functionality, structure and performance in large-scale OO software complex system.

Multi-objective optimization of a mixed-flow pump impeller using modified NSGA-II algorithm

In order to maintain a uniform distribution of pareto-front solutions, a modified NSGA-II algorithm coupled with a dynamic crowding distance(DCD) method is proposed for the multi-objective optimization of a mixed-flow pump impeller. With the pump meridional section fixed, ten variables along the shroud and hub are selected to control the blade load by using a three-dimensional inverse design method. Hydraulic efficiency, along with impeller head, is applied as an optimization objective; and a radial basis neural network(RBNN) is adopted to approximate the objective function with 82 training samples. Local sensitivity analysis shows that decision variables have different impacts on the optimization objectives. Instead of randomly selecting one solution to implement, a technique for ordering preferences by similarity to ideal solution(TOPSIS) is introduced to select the best compromise solution(BCS) from pareto-front sets. The proposed method is applied to optimize the baseline model, i.e. a mixed- flow waterjet pump whose specific speed is 508 min?1?m3s?1?m. The performance of the waterjet pump was experimentally tested. Compared with the baseline model, the optimized impeller has a better hydraulic efficiency of 92% as well as a higher impeller head at the design operation point. Furthermore, the off-design performance is improved with a wider highefficiency operation range. After optimization, velocity gradients on the suction surface are smoother and flow separations are eliminated at the blade inlet part. Thus, the authors believe the proposed method is helpful for optimizing the mixed-flow pumps.