Space Division Method Research Articles

Research on Foronline Short-Term Risk Assessment of Power System with Fast and Accurate Analysis Method Based on State Space Division

This paper proposed a state space division method to assess the online short-term risk of power system fast and accurately. This method divided all the possible operation system states into two mutually complementary subspaces according to the occurrence probability. In order to shorten the time-consuming, different method was used to calculate the risk of each subspace. Analytical method (AM) was used to calculate the risk of the first subspace comprised with the large occurrence probability states, which was identified using the Fast Sorting Technique (FST). System states that have a small occurrence probability comprised the second subspace, whose risk was calculated using Monte Carlo Simulation (MCS) combined with the adaptive importance sampling technique (AIST) and scattered sampling technique (SST). Through the case studies conducted on the MRTS, it is validated that the proposed method can assess the online short-term risk fast and accurately.

Sentiment Recognition of Online Chinese Micro Movie Reviews Using Multiple Probabilistic Reasoning Model

Online review websites provide an important channel for people to share their opinions. In this paper, we research the sentiment recognition technology on online Chinese micro movie reviews. As the sentiment expressed in Chinese is subtle and the feature space is very sparse, we adopt n-grams to develop sentiment feature space, and then propose an ensemble learning algorithm based on random feature space division method, namely Multiple Probabilistic Reasoning Model (M-PRM), for supervised document level sentiment classification. This algorithm captures discriminative sentiment features and makes full use of them. Comparing with this algorithm, we apply other four machine learning methods: Multinomial NaiveBayes (MNB), Probabilistic Reasoning Model (PRM), Sentiment-word method (SWM) and SVM on two micro movie review datasets. Results show that M-PRM achieves better classification performance than other methods.

Fast calculation approach to semi-empirical molecular orbital method using real space division method

The authors have developed a new approach for large-scale systems including over 100,000 atoms to obtain physical strength from the viewpoint of atom–atom bonding energy. Combining the semi-empirical molecular orbital method with real space division method makes it possible to estimate structural parameters, electronic structures and bonding energy for various large systems. With this method, various quantum physical properties can be obtained quickly using the semi-empirical molecular orbital method, while adopting real space division improves the computational efficiency of parallelization. In this study, the authors applied this method to SiH4 molecule and crystalline silica system, and carried out bond order and bonding energy analyses. In this analysis, the developed method offered almost the same analytical accuracy as the first principle method, while its calculation speed was much faster than that of the latter. The developed method was also suitable for parallel computing.

Numerical study of color holographic projection using space-division method

We propose a color holographic projection using the space-division method, which can reconstruct a two-dimensional color image by one hologram and avoid the superimposing of unwanted images on a wanted image. We calculated three holograms corresponding to red, green and blue, and then generated one hologram to add the three holograms. The three holograms were optimized by the Gerchberg-Saxton algorithm for improvement of reconstructed color images. We numerically evaluated the image quality of color reconstructed images in terms of the color space of YCbCr, and compared the quality of color reconstructed images by the space-division method with that of reconstructed color images using another color holographic projection method.

Task Space Division and Trajectory Planning for a Flexible Macro-Micro Manipulator System

This paper deals with a flexible macro-micro manipulator system, which includes a long flexible manipulator and a relatively short rigid manipulator attached to the tip of the macro manipulator. A flexible macro manipulator possesses the advantages of wide operating range, high speed, and low energy consumption, but the disadvantage of a low tracking precision. The macro-micro manipulator system improves tracking performance by compensating for the endpoint tracking error while maintaining the advantages of the flexible macro manipulator. A trajectory planning scheme was built utilizing the task space division method. The division point is chosen to optimize the error compensation and energy consumption for the whole system. Then movements of the macro-micro manipulator can be determined using separate inverse kinematic models. Simulation results for a planar 4-DOF macro-micro manipulator system are presented to show the effectiveness of the control system.