A military decision maker is typically confronted by the task of determining optimal course of action under some constraints in complex uncertain situation. Thus, a new class of Combinational Constraint Optimization Problem (CCOP) is formalized, that is utilized to solve this complex Operation Optimization Problem. The object function of CCOP is modeled by Influence net, and the constraints of CCOP relate to resource and collaboration. These constraints are expressed by Pseudo-Boolean and Boolean constraints. Thus CCOP holds a complex mathematical configuration, which is expressed as a 0 1 integer optimization problem with compositional constraints and unobvious optimal object function. A novel method of Genetic Algorithm (GA) combination of Boolean Constraint Programming (BCP) is proposed to solve CCOP. The constraints of CCOP can be easily reduced and transformed into Disjunctive Normal Form (DNF) by BCP. The DNF representation then can be used to drive GA so as to solve CCOP. Finally, a numerical experiment is given to demonstrate the effectiveness of above method.

An unsuitable representation will make the task of mining classification rules very hard for a traditional evolutionary algorithm (EA). But for a given dataset, it is difficult to decide which one is the best representation used in the mining progress. In this paper, we analyses the effects of different representations for a traditional EA and proposed a growing evolutionary algorithm which was robust for mining classification rules in different datasets. Experiments showed that the proposed algorithm is effective in dealing with problems of deception, linkage, epistasis and multimodality in the mining task.

Co-combustion of coal and natural gas is a promising technology in the production of active lime. For this technology, proper fuel proportion of coal and natural gas (α) is one of the key parameters that requires significant thought. By means of numerical simulation, contrast studies on co-combustion with five different fuel proportions were carried out. This paper firstly puts forward the models used to describe the system based on the actual conditions. Then, numerical simulation results were analysed in detail to illustrate the co-combustion process and the velocity and temperature distribution in the kiln. Finally, comparisons of high temperature region, char conversion, length of calcining zone, CO and NOx emission and total heat transfer rate to the material bed were made in order to make a decision on fuel proportion. Synthetically considering, α=30% is a balance between benefits and costs for the rotary lime kiln studied.

In the aviation industry, experts are enthusiastic over the research of sophisticated weapons. Little specialist pays attention to the innovation modes and methods. Up to now little quantization method suitable for aviation weapon systems innovation is presented. Base on the deep analysis and study on features of aviation weapon systems innovation and different innovation mode from the mass production, we have designed process model and quality chain model of aviation weapon systems innovation. Compared with the process model of large-scale innovation, the process models are more complex including many feedbacks and adding five steps: task decomposition, analysis of knowledge gap, accumulation of key knowledge, outsourcing selection, system integration. Meanwhile manufacturing process and R&D process are preformed simultaneously, and are involved in the process of module development. Technology application and diffusion are preformed with delivering the final innovation product to user. Quality function deployment and quality house are adopted to deal with the quality transfer among nodes. Quality demands of one node are converted into the technique features of another node in the quality house. We designed the top-down technique features transfer model and bottom-up demands transfer model to solve the quality transfer problems among nodes. At last an example is given to illustrate that this approach can accelerate to blaze the aviation weapon systems trails more than the existing methods and effectively reach quality management of aviation weapon systems innovation.

For researching properties of HJ-1A CCD camera multi-spectral data in performance on extraction of land features information, this paper selected the east area of NiLeke forest farm in the western Tianshan mountain as the study area, and analyzed different accuracies for HJ-1A CCD data in identifying forest land categories using various classification methods. Firstly, maximum-likelihood classifier, Mahalanobis distance classifier, minimum distance classifier and K-means classifier were used to category land use types with two different scales on HJ-1A CCD1 and Landsat5 TM images, and analyzed separately with confusion matrix. Secondly, forest land types were distinguished by texture information and the smallest polygon size using K-NN method based on clustering algorithm. The comparing results show: at first, different classification system have different accuracy. In the first land use classification system, the accuracy of HJ-1A CCD1 images are lower than TM images, but higher in the second land use classification system. Secondly, accuracy result of maximum-likelihood classification is the best method to classify land use types. In the first land use classification system, TM total accuracy is up to 85.1% and Kappa coefficient is 0.8. In the second land use classification system, the result is up to 85.4% and kappa coefficient is 0.74.Thirdly, judgment both from the view of visual interpretation and quantitative accuracy testes, non-supervised method with K-means classifier has low qualities where many land features have characters of scattered distribution and small different spectrum information. Finally, the experiment proved that there were good vector results on HJ-1A remote sensing image in the view of visual judgment, and extracted deferent forest land by the overall accuracy 87% with the supports by those variables’ distribution knowledge, such as conifer, mixed forest, broadleaf, shrubby.

High-dimensional indexing is a pervasive challenge faced in multimedia retrieval. Existing indexing methods applying linear scan strategy, such as VA-file and its variations, are still efficient when the dimensionality is high. In this paper, we propose a new access idea implemented on linear scan based methods to speed up the nearest-neighbor queries. The idea is to map high-dimensional points into two kinds of one-dimensional values using projection and distance computation. The projection values on the line determined by the first Principal Component are sorted and indexed using a B+-tree, and the distances of each point to a reference point are also embedded into leaf node of the B+-tree. When performing nearest neighbor search, the Partial Distortion Searching and triangular inequality are employed to prune search space. In the new search algorithm, only a small portion of data points need to be linearly accessed by computing the bounded distance on the one-dimensional line, which can reduce the I/O and processor time dramatically. Experiment results on large image databases show that the new access method provides a faster search speed than existing high-dimensional index methods.

The purpose of this paper is to study the numerical oscillations of Runge-Kutta methods for the solution of alternately advanced and retarded differential equations with piecewise constant arguments. The conditions of oscillations for the Runge-Kutta methods are obtained. It is proven that the Runge-Kutta methods preserve the oscillations of the analytic solution. In addition, the relationship between stability and oscillations are shown. Some numerical examples are given to confirm the theoretical results.

In this paper, motion differential equation of the two degrees of freedom(2-DOF) vehicle is established based on the linear two degrees of freedom vehicle model and is derived without simplifying the front wheel steering angle(FWSA), then we analyze the vehicle's steady-state response , transient response and the amplitude-frequency characteristic of yaw velocity under different FWSA with the help of the matlab software and finally compare the results with the simplified ones to determine how the FWSA influences the level of the vehicle handling and stability(VHS). At the same time in order to better improve the VHS, this paper proposes a set of active control theory to optimize vehicle’s steady-state performance.The results show that: while the FWSA is small, it has a less influence on vehicle handling and stability, the FWSA is large,it has a greater influence on vehicle handling and stability and the active control can make the vehicle in the best response state when it is in the steady-state.