Applied Mechanics and Materials Vols. 44-47

Abstract: Wireless sensor networks, which are energy limited, low hardware configuration and proneness to invalidation, puts a high demand on the positioning algorithm. Therefore the improved multidimensional scaling (IMDS) algorithm is proposed. In IMDS, firstly, local positioning areas (LPA) are established by an adaptive search algorithm. So the centralized multidimensional scaling (MDS) algorithm is changed into a distributed one. Then the shortest path distances between nodes on LPA are corrected with the geometric correction method (GCM) and adjusting weight correction method (AWCM). The distances between nodes become more accurate. Finally, with information of the public nodes of LPA and anchor nodes, we get the wireless sensor nodes coordinates through coordinate transformation by the SMACOF algorithm and the classical MDS algorithm.

Abstract: Minimum zone circle (MZC), minimum circumscribed circle (MCC), maximum inscribed circle (MIC) and least square circle (LSC) are four common methods used to evaluate circularity errors. A novel particle swarm optimization algorithm based on self-adapted comprehensive learning (ACL-PSO) is proposed to evaluate circularity errors with real coded strategy. In the algorithm, population learning mechanism and velocity mutation strategy are adopted. In the meantime, ACL-PSO is applied to the unified evaluation of circularity error. The experiment results evaluated by different methods indicate that the proposed algorithm not only converges to the global optimum rapidly, but also has good stability, and it is easy to generalize.

Abstract: Proposes a new domain-knowledge independent algorithm of discretization of consecutive attributes based on decisions to amend the limitation that Rough Sets can only deal with the discrete attributes in data sets. Unlike traditional methods, the candidate breakpoint set is obtained after the calculation and sorting of the attribute significance of each consecutive attribute thus leads to a smaller set size and less computational complexity. At the same time, proposes some rules of reducing candidate breakpoints in order to increase the velocity of system convergence. Using the algorithm, the decision table after discretization will be always consistent and can reserve useful information as much as possible. Finally, the algorithm is knowledge-independent and can be used in different fields without any additional information.

Abstract: Analyzes the traditional methods of extracting decision rules in Rough Sets, defines the concept of the decision dependability and proposes a novel algorithm of extracting short decision rules. Only the length of decision rules is extended when the current decision rules can’t classify all the samples in the decision table. At the same time, three methods are proposed to reduce the computational complexity: 1) defines the concept of bound coefficient, 2) only classify the samples with the same decision values at a time thus averting the time-consuming classification of the equivalence classes with different decision values, 3) defines the Remain set and only classify the samples in the Remain set, so the computational complexity will decrease proportional with the reduction of the samples in the Remain set. Above-mentioned methods can be used directly for incomplete information systems and have great practicability.

Abstract: Traditional image segmentation algorithms usually can’t obtain expected effects when facing with complex images such as container code images with complex backgrounds and bad illuminations. This paper introduces the definition of valid gradient and proposes a novel image segmentation algorithm based on it to solve above problem. Through statistical analyzing of the valid gradient information of the edges between the target and the background, some thresholds can be obtained directly and used to segment the images. The experiment results show that the algorithm can get better performance evaluation. Finally, the algorithm has good practicability and can be used directly in different image segmentation fields.

Abstract: The aim of regional traffic control optimization is to find the optimal design parameters while thinking over the route choice of users. This problem can be formulated as a bi-level programming program. In the program, signal control scheme and user equilibrium traffic assignment are optimized in the upper and lower level respectively. The solution procedure developed with the genetic algorithm has been tested with an example of factual road network.Numerical experiment verified the proposed model is quite promising for use in design of regional signal control.

Abstract: In order to solve the retrieval problem of design example in rapid response design, similarity computation model among design examples is given, computation of attribute weight of design example is done based on the method of uneven weight distance coefficient, computation of similarity between product structure model that meet the requirement of customers and design examples existed is done by the method of combination weight. This method has been applied in rolling guide conceptual design based on example inference, the result indicated that the weight computational method proposed is simple and the reliability is good, it can solve the intelligent retrieval problem of design examples in rapid response design.

Abstract: At first, this paper compared the present some advantages and disadvantages of reactive power compensation devices, and analysis the disadvantages of these devices in practical application deficiencies, then put forward a new kind of reactive power compensation principle. With the development of power electronic devices, this paper put forward a new type of reactive power compensation which based on RB-IGBT of SVC mode, synthesize the advantages of domestic reactive power compensation devices at present, and the prospect of application is very good.

Abstract: Molten metal carbon is an important parameter to be controlled during the BOF operation. In this paper, a fuzzy logic system for carbon sensing in a basic oxygen furnace (BOF) is presented. This objective system is identified from input-output data of the system by applying the subtractive clustering algorithm. The input data presents the optical radiations emitted from the BOF mouth and the output presents the carbon content of the molten metal contained in BOF in order to provide an efficient decision support application. The variables employed to develop the fuzzy logic system are obtained through an optical sensor located adjacent a full scale BOF at Nanjing steels’. Preliminary results are really encouraging.

Abstract: Aimed at the problem of reading and controlling UG files by OpenGL in VC++ environment, a method of object-oriented programming is proposed. The OpenGL single document, multiple documents and visualization windows are created by using the classified idea in VC++ environment. PRT format data files of UG are converted to DXF format data files. Not only the conversion rate but also the conversion quality of different format data file are ensured by using the intermediate conversion format CGM and the problems of redundancy lines and view missing are prevented. DXF files are converted to 3DS files by 3DS MAX software. Controlling and redrawing of UG files in OpenGL are realized. The Object-oriented method is better than process-oriented program design method on the reliability and operability of procedure. The method has been applied in the virtual CNC milling system and provided a theoretical basis for the development of visualization system.