Journal of Intelligent & Fuzzy Systems - Volume 31, issue 6

Authors: Wang, Xiaokan | Dong, Hairong | Sun, Xunbin | Yao, Xiuming

Article Type: Research Article

Abstract: As a typical, nonlinear system with instability, high order, strong coupling and multiple variations, the inverted pendulum model is the focus and research object of many experts and scholars in the control field. We propose the PD control method of the system based on the adaptive fuzzy compensation in order to weaken the impact of uncertainty in regards to external disturbances, as well as improve the precise control of the inverted pendulum system when the parameters are unknown. It uses the fuzzy method to conduct fuzzy approximation on the nonlinear system of the inverted pendulum by modeling the nonlinear inverted …pendulum system to weaken the impact of uncertainty and achieve complete compensation for the nonlinear system. Then, it establishes the adaptive PD fuzzy controller, forms the adaptive control law, applies the Lyapunov function to verify the stability and robustness of the system and finally achieves the intelligent, optimal control of the system. Simulation results show that the control method can achieve the optimal control of the tracking error and parameter error, has a better anti-interference ability and assures system stability. Show more

Keywords: Inverted pendulum, adaptive fuzzy control, compensation, nonlinear system

DOI: 10.3233/JIFS-169186

Citation: Journal of Intelligent & Fuzzy Systems, vol. 31, no. 6, pp. 3013-3019, 2016

Authors: Qian, Dianwei | Li, Chengdong

Article Type: Research Article

Abstract: This paper addresses a control scheme for formation maneuvers of a group of robots. The control scheme integrates an integral sliding mode (ISM) controller and a fuzzy compensator. The formation mechanism is leader-follower. The robots suffers from uncertainties. Chained to the uncertainties, the formation dynamics become uncertain. The control scheme needs to resist the formation uncertainties, meanwhile, the robots has to be formed up. Concerning the formation uncertainties, they are assumed to be unknown but bounded. Since they challenge the formation control, the fuzzy compensator is utilized to approximate them where an ISM-based adaptive law is deduced from the stability …analysis. In the sense of Lyapunov, not only the convergence of the approximation error can be guaranteed, but also such a control scheme can asymptotically stabilize the formation system. Compared to the results by the sole ISM control, some numerical simulations are presented to demonstrate the feasibility and performance of the control scheme. Show more

Keywords: Multiple robots, leader-follower mechanism, integral sliding mode control, fuzzy compensator, system stability

DOI: 10.3233/JIFS-169187

Citation: Journal of Intelligent & Fuzzy Systems, vol. 31, no. 6, pp. 3021-3028, 2016

Authors: Wei, Ming | Li, Yun

Article Type: Research Article

Abstract: An online regional bus scheduling model is proposed which focuses on the dynamic regulation of scheduling according to changes in the external environment, dynamic occurrences and periodic encounters of traffic incidents that interfere with the timely completion of vehicle trips. This paper employs fuzzy and random numbers to reflect uncertain delays as a result of meeting yard capacity constraints and other practical factors. A collaborative ant colony algorithm is employed to address the premature convergence defects of a traditional ant colony algorithm and to define the construct rules, pheromones, heuristic information and selection strategies of solutions. Finally, the validity of …the proposed model and algorithm is verified by a numerical example. Show more

Keywords: Online regional bus scheduling, regional problems, fuzzy and random travel time, collaborative ant colony algorithm

DOI: 10.3233/JIFS-169188

Citation: Journal of Intelligent & Fuzzy Systems, vol. 31, no. 6, pp. 3029-3037, 2016

Authors: Wei, Ming | Dai, Qiuxia

Article Type: Research Article

Abstract: Prediction of traffic emission is very important to management actions for traffic emission reduction. To overcome the shortcomings of ordinary prediction methods in previous studies, a novel model for the prediction of traffic emission is proposed for the combination of interval-valued intuitionistic fuzzy sets and case-based reasoning theory. Based on analysis of the factors that affect the traffic emission, a characteristic factor matrix of the source cases was constructed. Then, an interval-valued intuitionistic fuzzy set was introduced in order to describe the uncertainty of the case, and the source case that was the most similar to the target case, was …picked out by calculating the similarities between the source cases and the target case, therefore leading to the improvement in prediction accuracy. Finally, a case study was conducted to evaluate the effectiveness of the constructed prediction model. Show more

Keywords: Traffic emission, prediction, case-based reasoning, interval-valued intuitionistic fuzzy set

DOI: 10.3233/JIFS-169189

Citation: Journal of Intelligent & Fuzzy Systems, vol. 31, no. 6, pp. 3039-3046, 2016

Authors: Cui, Chunsheng | Jia, Hongfei | Huang, Liping | Zhang, Xiaopeng

Article Type: Research Article

Abstract: A fuzzy multivariate based line traffic prediction model and a station traffic proportion inference model are proposed in order to predict line entrance traffic and station traffic in the Shanghai subway system. The nonlinear autoregressive with external input (NARX) is adopted to predict subway line traffic. Correlative features that influence the line traffic time series are identified by time series trend analysis, including meteorological features, time features, and proportion of commuter passenger features. A time series correlation method and fuzzy c-means (FCM) is proposed to simplify the feature set by deleting the features of small coefficients between features and traffic …series. We determine the statistics of all stations’ traffic proportion of a subway line in order to construct a proportion matrix, and an eigenvector based station traffic proportion inference model is proposed to predict the future station traffic proportion, which is combined with the subway line traffic prediction results to realize subway station traffic prediction. We evaluate our model on the dataset of smart card records and weather condition dataset of one month in the Shanghai subway system. Experiment results confirm our proposed model’s advantages over baseline approaches. Show more

Keywords: Fuzzy time series, NARX, eigen recognition, subway traffic prediction, urban computing

DOI: 10.3233/JIFS-169190

Citation: Journal of Intelligent & Fuzzy Systems, vol. 31, no. 6, pp. 3047-3054, 2016

Authors: Xia, Guoqing | Luan, Tiantian | Sun, Mingxiao

Article Type: Research Article

Abstract: This paper proposes a new, comprehensive evaluation method of a principal, nonlinear fuzzy matter-element theory, which considers the complexity, hierarchy, contradiction and relevance of the factors in the sortie generation of carrier aircrafts. First of all, the index system of the sortie generation capacity is ascertained. The importance of the index is reflected in the degree of difference between the observed values of the index. Then the entropy value method is applied to determine the indexes’ weight. Secondly, in view of the situation that one index value is high and other index values are relatively low, the index with a …high value is classified as good or bad in the actual situation. However, the prominent effect of this index cannot be reflected. This is due to the shortage of weight and the weight average method. Thus, the evaluation result will not consort with the actual situation. Therefore, this paper uses the nonlinear fuzzy matter-element method to evaluate the first class indexes and the second class indexes. The problem that highlight influences of some indexes are difficult to deal with can be solved by using the nonlinear evaluation method. Finally, the Surge operation of the aircraft carrier “Nimitz” is taken as an example to evaluate the sortie generation capacity. The results verify the usefulness and reliability. Show more

Keywords: Fuzzy matter-element evaluation method, nonlinear fuzzy operator, entropy value method, sortie generation capacity of carrier aircrafts, comprehensive evaluation

DOI: 10.3233/JIFS-169191

Citation: Journal of Intelligent & Fuzzy Systems, vol. 31, no. 6, pp. 3055-3066, 2016

Authors: Wang, Zhanzhong | Zhao, Liying | Cao, Ningbo | Yang, Lina | Chen, Mingtao

Article Type: Research Article

Abstract: Due to the larger and larger proportion of hazardous material (hazmat) transportation occupying in the national economy, more and more researchers focus on this field. With the mature of fuzzy theory, this paper puts forward a model with three constraints, they are capacity, time window, risk respectively. It assumes that the travel time and the risk are both fuzzy variables, the risk is calculated by the affected people number multiply the accident probability. The goal is to obtain the best route schedule under the three constraints. This paper simultaneously designs the genetic algorithm based on fuzzy simulation. In the end, …two cases are given to illustrate the efficiency of the proposed model and algorithm. Show more

Keywords: Hazardous material (hazmat) transportation, fuzzy theory, three constraints, best route schedule

DOI: 10.3233/JIFS-169192

Citation: Journal of Intelligent & Fuzzy Systems, vol. 31, no. 6, pp. 3067-3074, 2016

Authors: Jin, Haiyan | Li, Yaning | Xing, Bei | Wang, Lei

Article Type: Research Article

Abstract: This paper proposes an efficient, bi-convex, fuzzy, variational (BFV) method with teaching and learning based optimization (TLBO) for geometric image segmentation. Firstly, we adopt a bi-convex, object function to process a geometric image. Then, we introduce TLBO to maximally optimize the length-penalty item, which will be changed under the teaching phase and the learner phase of the TLBO. This makes the length penalty item closer to the target boundary. Therefore, the length-penalty item can be automatically adjusted according to the fitness function, namely the evaluation standards of the image quality. At last, we combine the length-penalty item with the numerical …remedy mechanism to achieve better results. Compared with existing methods, simulations show that our method is more effective. Show more

Keywords: Geometric image segmentation, CV, BFV, TLBO

DOI: 10.3233/JIFS-169193

Citation: Journal of Intelligent & Fuzzy Systems, vol. 31, no. 6, pp. 3075-3081, 2016

Authors: Li, Xuefeng | Chen, Kai | Ruan, Junhu | Shi, Chenghua

Article Type: Research Article

Abstract: It has an important practical significance to assess the higher vocational education development level in one specific region, but few effective methods are reported in the literature. Based on the practical challenges, we propose a fuzzy TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) for assessing higher vocational education development levels. Firstly, in order to deal with decision-makers’ preferences on interval numbers, we develop a preference-based fuzzy number comparison method and then integrate it with the classic TOPSIS method to formulate a fuzzy TOPSIS method. An application example shows the effectiveness of the work and observes the impact of decision-makers’ …preferences on the assessment results. Several insights are also found to improve the assessment process in the real world. Show more

Keywords: Fuzzy number comparison, α-cut, fuzzy TOPSIS, higher vocational education, development level assessment, optimism degrees

DOI: 10.3233/JIFS-169194

Citation: Journal of Intelligent & Fuzzy Systems, vol. 31, no. 6, pp. 3083-3093, 2016

Authors: Shi, Baofeng | Chen, Nan | Wang, Jing

Article Type: Research Article

Abstract: Small private businesses provide employment for citizens. Their revenue and profit also contribute to GDP. Therefore, they are an important part of economic development in China. However, the key factor that can impede the development of small private businesses is financial problems. In order to solve this problem, we set up a credit rating model to analyze the credit status of small private businesses. The contributions of the paper are threefold. First, this paper introduces a novel technique that divides the customers’ credit ratings by using a fuzzy cluster analysis, as well as distinguishes the customer’s credit level by utilizing …a fuzzy pattern recognition approach, which is helpful to evaluate and predict the customer’s credit level. Second, the proposed model predicts the credit rating of a new loan customer by utilizing the lattice degree of nearness between the center vector of each credit rating and the data vector of a new loan applicant. This seems to offer a new insight into the credit rating of customers. Third, by utilizing the microfinance data of 2,157 Chinese small private businesses, the empirical results indicate that our research is not only significant for assessing the credit status in China’s small private businesses, but also serves as a useful tool for worldwide customers’ credit ratings. Show more

Keywords: Credit rating, fuzzy cluster, fuzzy pattern recognition, microfinance, small private business

DOI: 10.3233/JIFS-169195

Citation: Journal of Intelligent & Fuzzy Systems, vol. 31, no. 6, pp. 3095-3102, 2016