Supervised and Reinforcement Evolutionary Learning for Wavelet-based Neuro-fuzzy Networks

This study presents a wavelet-based neuro-fuzzy network (WNFN). The proposed WNFN model combines the traditional Takagi–Sugeno–Kang (TSK) fuzzy model and the wavelet neural networks (WNN). This study adopts the non-orthogonal and compactly supported functions as wavelet neural network bases. A novel supervised evolutionary learning, called WNFN-S, is proposed to tune the adjustable parameters of the WNFN model. The proposed WNFN-S learning scheme is based on dynamic symbiotic evolution (DSE). The proposed DSE uses the sequential-search-based dynamic evolutionary (SSDE) method. In some real-world applications, exact training data may be expensive or even impossible to obtain. To solve this problem, the reinforcement evolutionary learning, called WNFN-R, is proposed. Computer simulations have been conducted to illustrate the performance and applicability of the proposed WNFN-S and WNFN-R learning algorithms.     

基于表格语义的Web信息抽取方法的研究

在Web页面常用到表格这种元素。本文提出一种根据表格语义来进行信息抽取方法。首先提出了一种短语语义相似度的度量方法,然后利用短语语义的相似度确定表格标题行(列),并对表格行(列)与抽取字段的对应关系进行计算,最后计算表格的整体语义,度量该表格与所要抽取的内容有多大相关度。     

Matrine Exerts a Strong Anti-Arthritic Effect on Type II Collagen-Induced Arthritis in Rats by Inhibiting Inflammatory Responses

To investigate anti-arthritic effects of matrine isolated from the roots of S. flavescens on type II collagen-induced arthritis (CIA) in rats and to explore its related potential mechanisms, CIA rats were established and administered with matrine (20, 40 or 80 mg/kg/days, for 30 days). Subsequently, blood was collected to determine serum levels of TNF-α, IL-1β, IL-6, IL-8, IL-17A, IL-10, MMP-2, MMP-3 and MMP-9, and hind paws and knee joints were collected for histopathological examination. Furthermore, indices of the thymus and spleen were determined, and synovial tissues were collected to determine the protein expressions of p-IκB, IκB, Cox-2 and iNOS. Our results indicated that matrine significantly suppressed inflammatory reactions and synovial tissue destruction. Matrine inhibited paw swelling, arthritis indices and weight loss in CIA rats. Additionally, matrine decreased the levels of TNF-α, IL-1β, IL-6, IL-8, IL-17A, MMP-2, MMP-3 and MMP-9. Matrine also down-regulated expressions of p-IκB, Cox-2, and iNOS but up-regulated IκB in synovial tissues in CIA rats. The results suggested matrine possesses an anti-arthritic effect in CIA rats via inhibiting the release of pro-inflammatory cytokines and proteins that promote the NF-κB pathway.     

Efficient reinforcement learning through dynamic symbiotic evolution for TSK-type fuzzy controller design

In this paper, efficient reinforcement learning through dynamic-form symbiotic evolution (DSE) is proposed for solving nonlinear control problems. Compared with traditional symbiotic evolution, DSE uses the sequential search-based dynamic evolution (SSDE) method to generate an initial population and to determine dynamic mutation points. Therefore, better chromosomes will be initially generated while better mutation points will be determined for performing dynamic mutation. The proposed DSE design method was applied to different control systems, including the cart-pole balancing system and the water bath temperature control system, and control problems were simulated on these systems. The proposed DSE method was verified to be efficient and superior for solving these control problems and from comparisons with some traditional genetic algorithms.     

Non-linear system control using a recurrent fuzzy neural network based on improved particle swarm optimisation

This article introduces a recurrent fuzzy neural network based on improved particle swarm optimisation (IPSO) for non-linear system control. An IPSO method which consists of the modified evolutionary direction operator (MEDO) and the Particle Swarm Optimisation (PSO) is proposed in this article. A MEDO combining the evolutionary direction operator and the migration operation is also proposed. The MEDO will improve the global search solution. Experimental results have shown that the proposed IPSO method controls the magnetic levitation system and the planetary train type inverted pendulum system better than the traditional PSO and the genetic algorithm methods.     

An ART-based fuzzy adaptive learning control network

This paper addresses the structure and an associated online learning algorithm of a feedforward multilayer neural net for realizing the basic elements and functions of a fuzzy controller. The proposed fuzzy adaptive learning control network (FALCON) can be contrasted with traditional fuzzy control systems in network structure and learning ability. An online structure/parameter learning algorithm, FALCON-ART, is proposed for constructing FALCON dynamically. It combines backpropagation for parameter learning and fuzzy ART for structure learning. FALCON-ART partitions the input state space and output control space using irregular fuzzy hyperboxes according to the data distribution. In many existing fuzzy or neural fuzzy control systems, the input and output spaces are always partitioned into “grids”. As the number of variables increases, the number of partitioned grids grows combinatorially. To avoid this problem in some complex systems, FALCON-ART partitions the I/O spaces flexibly based on data distribution. It can create and train FALCON in a highly autonomous way. In its initial form, there is no membership function, fuzzy partition, and fuzzy logic rule. They are created and begin to grow as the first training pattern arrives. Thus, the users need not give it any a priori knowledge or initial information. FALCON-ART can online partition the I/O spaces, tune membership functions, find proper fuzzy logic rules, and annihilate redundant rules dynamically upon receiving online data     

Navigation Control of Mobile Robots Using an Interval Type-2 Fuzzy Controller Based on Dynamic-group Particle Swarm Optimization

International Journal of Control, Automation and Systems - This paper presents an effective navigation control method for mobile robots in an unknown environment. The proposed behavior manager (BM)...     

响应面法优化羊肚菌中蛋白质的提取工艺

目的采用响应面法优化羊肚菌蛋白质的提取工艺。方法通过超声波辅助提取羊肚菌蛋白,以蛋白得率为指标,考察超声温度、超声时间、料液比和pH对羊肚菌蛋白得率的影响。在单因素的基础上通过Box-Behnken试验对提取工艺试验进行优化试验。结果超声波辅助提取羊肚菌蛋白的最佳工艺条件为:料液比1:50 (g:mL)、超声时间60 min、提取温度60℃、pH 12,在此条件下蛋白得率为(32.56±0.50)%,与预测值32.99%接近。通过响应面分析得到的多元二次回归方程Y=32.56+0.97A 1.21B~+1.24C 0.2AB 1.07AC 1.45BC 1.86A~2 4.26B~2 1.87C~2,该模型可较好地预测羊肚菌蛋白得率,其中各因素对蛋白质得率影响的大小依次为:pH超声温度超声时间。结论本研究为羊肚菌蛋白的提取提供基础。     

A detector setup for the measurement of angular distribution of heavy-ion elastic scattering with low energy on RIBLL

A detector setup for the measurement of angular distribution of heavy-ion elastic scattering at energies around Coulomb barrier on the radioactive ion beam line in Lanzhou at the heavy-ion research facility in Lanzhou is designed.The beam profile and the scattering angles on the target are deduced by two parallel plate avalanche counters,and four sets of detector telescopes (including doublesided silicon strip detectors) are placed systematically with the beam line,incorporating with Monte Carlo simulations.The data of 16O on 89y target were analyzed to compare with the simulation results.It is found that the simulated distribution is agreeable with the experimental data.By assuming the pure Rutherford scattering at small scattering angles,the angular distribution of elastic scattering of 16O + 89y at low energies can be reasonably obtained.It indicates that this set of detector setup can be used for the measurement of angular distributions of heavy-ion elastic scattering at energies around Coulomb barrier.     

Image contrast expand enhancement system based on fuzzy theory

Microsystem Technologies - In the current age of information explosion, the extraction of relevant data from a large information pool, which includes images, has become crucial. Because of the easy...