A nonlinear model predictive control (NMPC) algorithm based on a BP-ARX combination model is proposed for multivariable nonlinear systems whose static nonlinearity between inputs and outputs could be obtained. The dynamic behavior of the system is described by a parameter varying ARX model, whose parameters...

The paper analyzes the key concepts, theories and methods of machine learning ensemble, and reviews the related studies on support vector machine (SVM) ensemble. The experiments on the remote sensing classification show that SVM ensemble is more accurate than single SVM. To obtain an effective SVM ensemble,...

To evaluate the enterprises' strategic management performance scientifically and accurately, this paper proposes the improved BP neural network model which imports the adjustable activation function and the Levenberg-Marquardt optimization algorithm. The improved model not only can simulate the expert...

Focused crawlers are programs designed to selectively retrieve Web pages relevant to a specific domain for the use of domain-specific search engines. Tunneling is a heuristic-based method that solves global optimization problem. In this paper we defined Gray Tunneling and use content block algorithm...

Many cardiovascular diseases such as hypertension, artherosclerosi are subject to remodel the characteristics of vascular wall; at the same time, this change is able to result in a counteractive with these diseases. It is significant to find out vascular pathological changes as early as possible. In...

The thesis puts forward an improvement method for the combining rule of Dempster-Shafer evidence theory based on the correlation between evidences. Different from D-S theory, the correlation coefficient between evidences is introduced; and varies with the evidence fusion. By decreasing the probability...

Computational complexity is one of the most important issues while dealing with the training of Support Vector Machines(SVMs), which is done by solving corresponding linear constrained convex quadratic programming problems. The state-ofthe- art training of SVMs takes iterative decomposition strategies...

In this paper, Genetic Algorithm (GA) is used to train the parameters of Discrete Hidden Markov Model (DHMM). To overcome the premature convergence in GA, a chaotic migration strategy is introduced to the pseudo parallel genetic algorithm to increase the diversity of population. Because the GA’s evolution...

This paper studied an ordering problem under non-stationary setting. It used the online algorithm with risk-reward that is a combination of probability analysis and classical online algorithm. We obtained an online risk base stock policy whose risk was restricted to a tolerance level by designing online...

Recommender Systems are applications that have emerged in the e-commerce area

The evaluation processes are used for quality inspection, marketing and other fields in industrial companies. This contribution focuses in sensory evaluation where the evaluated items are assessed according to the knowledge acquired via human senses by a panel of experts. In these evaluation processes...

XCS has been used in several fields as a prediction engine before; its population based nature enables XCS to generate sets of properly pruned classification rules. Further, unlike other population based algorithms, it learns using rewards. These properties encouraged us to use it as a predictor engine...

In this paper the Fuzzy DEA Model was constructed. The model conducted an X-efficiency measure on Chinese Commercial Banks. At last Cause analyses and policy suggestions was given.

Learning is obtaining an underlying rule by using training data sampled from the environment. In many practical situations in inductive learning algorithms, it is often expected to further improve the generalization capability after the learning process has been completed if new data are available. One...

In this article, we demonstrate the problem of synchronization for a class of chaotic systems with different structure and unknown parameters. A nonlinear controller is developed. We estimate the parameters and construct the proper controller with these estimations. It is also found that this scheme...

As a filter model, rough set-based methods are one of effective attribute reduction(also called feature selection) that preserve the meaning of the features. In rough set theory, researchers mainly focus on extension of the classical rough set model(also called Pawlak model for short) and development...

When the citizens make traffic mode choice, the bus and taxi are always abandoned for long waiting time, especially during the peak time. In view of this, this paper defines the concept of the travel time budget and the reliability of travel time. A traffic mode choice is proposed, considering four factors:...

This paper presents a novel simple, but efficient robot path planning algorithm, which plans the obstacle-avoidance path according to map information, makes robots reach the target. In the paper, the actual environment is discretized into a topologically organized map consisting of targets, obstacles...

Different from the general way to overdetermined blind source separation problem whose demixing matrix is a nonsquare one just as the mixing matrix, this paper proposed that using n (the number of sources) elements of the mixture signals as the new mixture signals to be separated, this means, the dexmixing...

Logistics service project evaluation is a key step in project management. The evaluation tasks are not only covered by the whole project process, but also are perceived by characteristic of logistics service. According to project management’s hierarchical approach, we propose two evaluations in the theory...

Enterprise credit rating is an important issue in finance field. Small and Medium Enterprises are playing more and more important role in world economy development. Especially, China SMEs has gained rapid development in recent years. However, financing difficulty is a predominant and common problem for...

In this paper we briefly present the concepts of ontology and Web Service, analyze the advantages that introduce them into robot control system, provide a remote control system of robot based on ontology and Web Service. This research constructs the Ontologies related with the control parameters of machine...

An adaptive method for predicting short-time traffic flow, which is based on phase space reconstruction and Volterra series, was proposed. We first employed Lyapunav exponent method based small data sets to validate that chaos exists in traffic flow. Then, phase space reconstruction for traffic flow...

It is very difficult to solve the large-scaled in the semiconductor device simulation, sparse and ill-conditioned matrix equation exactly and quickly. So the particle swarm optimization algorithm(PSO) based on the swarm intelligent technology is presented to get the global optimal solution of the matrix...

For the reason of different images with different space distribution of gray levels, we proposed a texture representation based on simplified pulse coupled neural networks (PCNN) model which output a series of binary images corresponding to different gray levels. Then we transformed the images into 1D...

Intelligent decision support system performance depends on knowledge base quality. With the decision problem and knowledge base becoming more complicated, it is necessary to provide effective method to optimize the management of knowledge base. Based on detailed analyzing of running characteristics and...

Map matching is a technique combining electronic map with locating information to obtain the real position of vehicles in a road network.This paper provides an overview on the map matching technique and its applications,and discusses some typical algorithms with experiments analysis.

As we known, ants are blind and single ant’s capacity is limited. But researchers have studied that ant colonies have egregious ability to search shorter path which loads between their nests and foods. Inspired from this and based on ant colony optimization(ACO), we propose a new approach about attributes...

With respect to multiple attribute decision making problems with interval-valued intuitionistic fuzzy information, some operational laws of interval-valued intuitionistic fuzzy numbers, score function and accuracy function of interval-valued intuitionistic fuzzy numbers are introduced. An optimization...

In emotion recognition, many irrelevant and redundant features will affect recognition results, so feature selection is necessary. Aimed at emotion physiological signal feature selection, this paper proposed with improved discrete binary particle swarm optimization(BPSO) to increase the correct classification...

By the methods of bioinformatics, the sequences of HCV E2 protein from all the genotypes are studied on the variation and the B-cell epitopes. We find that even in the HVR1 and HVR2 regions, there are also some conservative sites, such as T2, G6, G23, and Q26, all of which belong to polar R-base amino...

Aiming at the trouble of easy getting into local minimum in quantum genetic algorithm, this paper presents a new hybrid quantum genetic algorithm. Using the method of mutative scale chaos optimization strategy, chaotic search for optimization is implemented to the colony which has been processed one...

Correlation analysis is a basic problem in the field of data stream mining. Traditional method is not suitable for real time processing with huge amount of stream data. We propose a new method based on Boolean representation for lag correlation analysis among multiple data streams. The raw stream sequence...

In this paper, we propose a novel scheme for speech emotion recognition, which uses decision-templates ensemble algorithm (DT) to combine base classifiers built on segment-level feature sets. Different feature sets from segments can provide sufficient diversity among base classifiers, which is known...

A class of Cohen-Grossberg neural networks with distributed delays are considered. By using the coincidence degree theorem and differential inequality techniques, sufficient conditions for the existence and exponential stability of the periodic solutions are established, Without assuming the boundedness,...

The ant system is a metaheuristic developed for the solution of hard combinatorial optimization problems. In this paper, through an analysis of the constructive procedure of the solution in the Ant Colony System (ACS), a modified algorithm for solving Vehicle Routing Problem (VRP), based on the ACS Hybridized...

In this paper, cluster analysis based on distance function [1] is investigated, then a clustering algorithm is created for the objects in formal concept context, analysis is a field of applied mathematics based on mathematical analysis of concept and conceptual hierarchy, under this clustering, we only...

Text classification can efficiently enhance the text processing capability by automatically sorting out them according to defined collection of categories. This paper uses TFIDF method to represent documents, and set the NGramSize value to be 6. Word Frequency vector is used to measure and distinguish...

In an open electricity market, electricity purchasers will trade in two different ways of marketing. Contract and power auction market, a typical decision-making issue is how to determine purchasing proportion of two markets to reduce purchase expenses and avoid risks. Based on chance constrained programming,...

E-business intelligence and reliability are the crucial step for companies’ huge volume data processing. This paper presents a transaction middleware and web server working together supported by business intelligence mechanism, which can get a reliable scaleable plug-in based system. The efficiency of...

Nowadays, the change of marketplace require manufacturing system to diversify from mass customization style to step-mass customization style, thus lead to the manufacturing value orientation change from product oriented to custom oriented, main manufacturing strategy change from cost, quality etc. to...

In RGB space, the paper optimizes the algorithm of median filter. Not only it could keep its original filter capability, but also it makes the quantity of algorithm decrease greatly. The paper puts forward a standard to identify fire based on the fire edge wobbling-sharp features standard. There are...

Machine learning methods are promising tools to transient stability assessment (TSA) of power system. Support vector machine (SVM) is used to assess the transient stability of power system after faults occur on transmission lines. Single machine attributes were studied as inputs of the SVM classifier....

Improving the smooth degree of modeling data series is key factor of grey model’s precision. According to function transformation theory and grey system modeling theory, elementary study on GM(1,1) model based on function ransformation is given, and the methods of linear function transformation and compound...

In this paper, we will provide a method for solving group decision-making problems based on IOWA operators. In which, linguistic assessments of decision makers could be selected freely, i.e., let S={s1, s2, ..., sn} be basic linguistic assessments, decision maker could select his (or her) linguistic...

Gene expression data has been used to analyse and classify disease in resent years. Combining the attribute importance in Rough Sets Theory and entropy in Information Theory, this paper introduces the study of the gene analysis and selection method. A novel algorithm, called RMSME, is proposed to use...

A method for multi-class and multi-label automated text categorization based on twin-SVM with naïve Bayes ensemble is proposed. Twin-SVM classifiers give a solution to the multi-label problem. For multi-class situation, naïve Bayes classifier constrains the belonging scope of a testing sample within...

IOWA operator, which is proposed by Yager, et al, has been used in many fields. In the paper, we deal with group linguistic assessments decision-making problems based on IOWA. Firstly, in the homogeneous, the higher the consistence degree of experts is, the higher the weights of linguistic assessments...

The quality of the data affects the usability of the data mining’s results. Making a data preparation before the mining can improve the quality. If the data are collected from the multi-data source, data preparation becomes very difficult. In this paper, a data-cleaning method based on the association...

Complex industrial processes such as nuclear power plants, chemical plants and petroleum refineries are usually equipped with alarm systems capable of monitoring thousands of process variables and generating tens of thousands of alarms which are used as mechanisms for alerting operators to take actions...

Marriage in Honey Bees Optimization (MBO) is a swarm-intelligence method. To improve its optimization performance, the Nelder-Mead method is used combined with MBO. The paper proposed an improved Marriage in Honey Bees Optimization algorithm. The local characteristic is obtained by Nelder-Mead Method...

This paper takes integrated optimization of Material Requirements Planning (MRP) and Capacity Requirements Planning (CRP) as research intention, builds a novel multi-objective optimization algorithm of MRP and CRP based on genetic evolution, and designs the proper genetic operators which take the integrated...

Although organization oriented paradigm is a promising way to design dynamic interactive computational systems in open and heterogeneous networked environment, there is still lack of a suitable formal approach to support this paradigm. RBA, a boxed ambient calculus extended with separated regulating...

The paper proposes an attack pattern ontology and formal framework for network traffic anomalies detection within a distributed multiagent Intrusion Detection System (MUDIDS) architecture. The role of traffic anomalies detection is discussed then it has been clarified how some specific values characterizing...

Fishery prediction by using long-term accumulated hydrology elements and catch statistic data has been an urgent requirement in aquatic domain. In this paper, 18 different WCPO (Western and Central Pacific Ocean) hydrology elements were collected and a key influence element set was found by using Rough...

A method to recognize the channel siltation using support vector machine (SVM) was developed. The method was based on the system that the transducer arrays were laid out respectively on each side of the channel. Through the analysis of sonar signal acquired by data acquisition unit, the features to recognize...

In this paper, a hybrid intelligent system, combining rough set approach and fuzzy support vector machine (FSVM), is applied to the study of credit risk assessment in commercial banks. We can get reduced information table, which implies that the number of evaluation criteria such as financial ratios...

It has been a long harassment to seamless tubes production that its productivity will be largely affected by the pause caused in adjusting the craft parameters of piercer, the important equipment in the process. Aiming at the problem, a rebuilding method of Diescher guide disc is proposed. The on-line...

When the information management system is carried into execution, the unstructured video data always cannot be organized properly. Traditional analytical method by handling large number of video shots cannot convey meaningful semantics. We divided the video into appropriate shots with the improved twin-comparison...

Euclidean distance, Hausdorff distance and SSP distance are discussed, and SSP distance is used for improved Isomap algorithm. Two methods are put forward for improving Isomap algorithm. One is aligning input data of original Isomap algorithm, the other is modifying Isomap algorithm itself. SSP distance...

The chaotic behavior of groundwater depth time series is investigated using correlation dimension method and the CAO method based on the reconstruction of phase-space. A groundwater depth time series, each five days series of 25 years (with a total of 1793 values) observed in Hetao irrigation district...

Multiple sequence alignment (MSA) has become an essential tool in the analysis of biologic sequences. In this paper, an artificial immune system (AIS) is proposed to train hidden Markov models (HMMs). Further, an integration algorithm based on the HMM and AIS for the MSA is constructed and a decoding...

In illustration to high computational complexity of the genetic algorithm-based FCM clustering algorithm, combining with traditional genetic algorithms and FCM algorithm, an improved GFCA algorithm with serial number coding is proposed in this paper. The simulations of two standard data sets for the...

Data classification is a very important point in Data Mining,but the existing classification algorithms always only discover the classification rules with high accuracy,and the research about interesting classification rules is few. So this paper proposed an algorithm to find the interesting classification...

The batch-to-batch model-based iterative optimal control strategy for batch processes is realized based on multilayer recurrent fuzzy neural network (MRFNN) and chaotic search. MRFNNs are used to model batch processes. Modeling and optimization problems are mainly solved by chaotic search. Due to model-plant...

The paper combines the passenger behavior with the decision of administrative department based on multi-agent simulation method of complex system theory, considering each advantage of CA and multi-agent, with the entrance of administrative departments and passenger behavior. In the passenger organization...

Most of the current fuzzy ontologies are too domain-specific and don’t support reasoning on fuzzy descriptions. By investigating the uncertainty information in the real world, we discover three widely existing general fuzzy relations. Based on such investigation and motivated by the desire to support...

After an introduction of the principle of particle swarm optimization (PSO) algorithm based on swarm intelligence, and of the modified version of the PSO algorithm, a neural network system for gearbox fault diagnosis has been established. After being trained by PSO algorithm, the neural network system...

It’s a hot research issue to integrate information technology into the Government Resource Planning (GRP). The indices of current GRP system are just with expression of “investment” form which is disconnected with “output” form for control indices and “result” form for evaluation indices. Thus the current...

Security protocols have been recently found with subtle flaws due to incomplete or ambiguous specification. Although formal methods have remarkably assisted in protocol analysis, they ignores the effect of hostile/uncertain environment, which might lead to inconsistent belief that can be held by principals...

It is hard to set up catastrophe potential function by using conventional methods and choose control variables of catastrophe potential function. So the method of setting up potential function is given to analyze the brittleness of complex system by means of relations among systems. The feasibility of...

This paper proposes a method for extracting features of target object automatically in a pose-measuring system. A tag stuck to the target object is designed to make the system more robust and precise. First, detect all the corners of an image. Then, geometric invariants, which are formed by several invariants...

Nowadays, during rocket launch, the decision-making partly depend on the results of the rocket status inspection. But we know the fast and precisely detect and diagnose of rocket faults is a conflict problem in many cases of bulk information processing. In this paper three methods are proposed. First,...

A hybrid of artificial fish swarm algorithm (AFSA) and particle swarm optimization (PSO) is used to training feedforward neural network. After the two algorithms are introduced respectively, the hybrid algorithm based on the two is expressed. The hybrid not only has the artificial fish behaviors of swarm...

The Computer Generated Force (CGF) has decision ability by self-learning mechanism, which is an important research field in applying machine learning technology to military simulation. On the basis of modeling architecture of Agent and Learning Classifier Systems (LCSs) technologies, a learning behavioral...

In this paper, we first propose a computational model. Then on the basis of two virtual knowledge networks constructed, we investigate how diverse connecting mechanisms between network A and B differentially influence the co-evolution of the knowledge levels of both networks. The simulation results indicate...

This paper firstly discussed the problem of independent tasks scheduling on tree network, where resources have different speeds of computation and communication. And then analyzed the property of tree-shaped logical network topologies, presented an integer linear programming for this problem, and a heuristic...

We begin the paper studying the axioms that the inclusion measure of an element in another element of a lattice and the similarity measure between two elements should satisfy. Next, we present a series of expressions of inclusion measures, ¯rst for intuitionistic values and then for intuitionistic fuzzy...

Based on T-S fuzzy model, the robust guaranteed cost control problem is studied for a class of uncertain singular systems with state and input delays. Sufficient conditions are provided for the construction of a state feedback guaranteed cost controller. These conditions are given in terms of the feasibility...

The various-density problem has become one of the focuses in density based clustering research. A novel dispersive degree based algorithm combined with classification, called CDDC, is presented in this paper to remove the hurdle. In CDDC, a sequence is established for depicting the data distribution,...

Optimization of multi-flight refueling service scheduling is very important for the recovery efficiency of flight delays. After analyzing the constraints and objective of multi-flight refueling service scheduling problem, a model is put forward. A novel particle swarm optimization is designed to solve...

Ignoring the samples far away from the training samples, our study team gives a new norm-based derivative process of localized generalization error boundary. Enlightened by the above research, this paper proposes a new method to construct radial basis function neural networks, which minimizes the sum...

This paper uses GAssist system to get symbolic rules and proposes four techniques to improve it. A new population initialization method is applied and fitness scaling is used to promote the population’s convergence. It also improves on the deserted hierarchical selection operator and combines it with...

System identification is a fundamental topic of control theory, and LS-SVM has been applied to system identification. An online training algorithm of LS-SVM for system identication is presented, which is suitable for the data set supplied in sequence rather than in batch. The online algorithm avoids...

In this paper, the fuzziness of Gomoli¶nska approximation space based on uncertainty mappings was introduced. It is proved that many approximation operators could be constructed by the composition of basic approximation operators.

A robust sliding mode control (SMC) is presented for uncertain systems with a state-delay. Based on linear matrix inequalities (LMI), a delay-independent sufficient condition is developed for the design of a stable sliding mode plane in term of virtual state feedback controller. A simple controller is...

This paper discusses the synchronization of uncertain Lü chaotic systems. Based on the idea of active control, a novel active pining control strategy is presented, which only need a state of uncertain Lü chaotic systems. This controller can achieve synchronization between a salve system and a master...

This paper investigates the problem of static output feedback stabilization for a class of uncertain linear singular time-delay systems. Firstly, based on the stability criterion for the nominal singular time-delay system, a sufficient condition for the existence of the static output feedback controller...

Based on the concept of incompatible factor, this paper introduces further the principle of minimal incompatibility, and use this principle to improve the triple I method. In addition, by the principles of maximal support and minimal incompatibility the solvings of the problems of Fuzzy Modus Ponens...

An expert system for workflow procedure optimization is proposed in this paper, in which the optimization method of the workflow procedure is presented with the workflow management system (abbr. WfMS). The running analysis of WfMS is the inputs of expert system, the optimization report and the regulation...

CNC integrated inspection is an important component for monitor and diagnosis in integrated manufacturing process, and is a pivotal step avoiding grave incidents timely and effectively. Combined with the methods used before in the CNC integrated inspecting plan, an improved domain ontology knowledge...

Coalition formation is an important manner of communication among agents in MAS. Some previous works only pay attention to forming a coalition for each task respectively, and the gross income of MAS may be not maximal. Thus, combination task called task-group is originally taken into account. In this...

Robotic vehicle navigation in unstructured and uncertain environments is still a challenge. This paper presents the implementation of a multivalued neurofuzzy controller for autonomous ground vehicle (AGVs) in indoor environments. The control system consists of a hierarchy of mobile robot using multivalued...

An adaptive steganographic scheme is proposed in this paper. The adaptive quantization embedder is introduced and employed by block-wised fashion. We also constructed contrast-correlation distortion metric to optimally choose quantization steps for image blocks to guarantee more data being embedded in...

Based on the metaphor of specialization and cooperation in hierarchical social organization, a new particle swarm optimization (PSO) algorithm, hierarchical subpopulation PSO (HS-PSO), was proposed. In HS-PSO, the entire population is divided into several subpopulations which are arranged in a hierarchy....

The Self-Assessment Manikin (SAM) is an universally used instrument of pictographic non verbal measure which is used in many emotional studies in the field of the Psychology. In these emotional studies the usual aggregation operator is the classical mean. In this paper, a new aggregation operator is...

In this paper, we propose a hybrid approach, which is a statistical machine translation (SMT), while using an example-based decoder. In this way, it will solve efficiently the re-ordering problem in SMT and the problems for spoken language MT, such as lots of omissions, idioms etc. We present a novel...

The hydraulic model is an important experiment system for studying the hydrological characteristic of river, lake and choosing the engineering project of port, dam and sea-route. The quality of the hydraulic model tests mainly lies on the measurement and control technology. This paper presents a hydraulic...

In this paper, we introduce an evolutionary immune method to solve the problems from dynamic data mining. We first present a new concept to describe our specific problem domain. Then, we identify the evolutionary immune mechanism in KDD by illustrating how the elements involved in the domain could be...

The satisfaction of ultimate customer can measure with four gross criteria in the supply chain, and can subdivide into ten sub-criteria. Customer satisfaction mainly performs from customer, so there is certain preference as a weight to each criterion. The weight is difficult to focus on one point, but...