International Journal of Computational Intelligence Systems

Power demand forecasting is important for economically efficient operation and effective control of power systems and enables to plan the load of generating unit. The purpose of the short-term electricity demand forecasting is to forecast in advance the system load, represented by the sum of all consumers...

The most difficult but important problem in advance driver assistance system development is how to measure and model the behavioral response of drivers with focusing on the cognition process. This paper describes driver's deceleration and acceleration behavior based on driving situation awareness in...

Complex T-spherical fuzzy 2-tuple linguistic set (CTSF2-TLS), which is a combination of complex fuzzy set (CFS), T-spherical fuzzy set (TSFS), and 2-tulpe linguistic variable set (2-TLVS), is a proficient technique to express uncertain and awkward information in real decision-making. CTSF2-TLS contains...

The Negative Selection Algorithm (NSA) is a kind of novelty detection method inspired by the biological self/nonself discrimination principles. In this paper, we propose two new schemes for the detectors re-editing and censoring in the NSA. The detectors that fail to pass the negative selection phase...

This paper introduces a novel concept of web-spreadsheet, which extracts product information by crawling through related web pages and generates information like a spreadsheet where each row represents product information and each column represents product attributes. Using Decision Tree based classifier,...

Comparing ear photographs is considered to be an important aspect of disaster victim identification and other forensic and security applications. An interesting approach concerns the construction of 3D ear models by fitting the parameters of a ‘standard’ ear shape, in order to transform it into an optimal...

Support vector machines (classification and regression) are powerful machine learning techniques for crisp data. In this paper, the problem is considered for interval data. Two methods to deal with the problem using support vector regression are proposed and two new methods for evaluating performance...

Success of an e-business company is strongly associated with the relative quality of its website compared to that of its competitors. The purpose of this study is to propose a multi-attribute e-business website quality evaluation methodology based on a modified fuzzy TOPSIS approach. In the proposed...

Information retrieval systems like web search engines can be used to meet the user’s information needs by searching and retrieving the relevant documents that match the user’s query. Firstly, the query is inputted to the web search engine and assumed to be a good representative for the user’s intention...

Considering the low degree of abstraction of traditional shape grammar in national pattern reuse design, this paper proposes a method based on the combination of improved shape grammar and an optimization algorithm to reuse national patterns design. As an application example, we carried out research...

Computing object distance using image processing is an important research area in the field of computer vision and robot navigation applications. In this paper we have proposed a new method to compute the distance of an object using a single image. According to our observation there exists a relationship...

In social networks, counting the number of different cycle sizes can be used to measure the entropy of the network that represents its robustness. The exact algorithms to compute cycles in a graph can generate exact results but they are not guaranteed to run in a polynomial time. We present an approximation...

Communication technology and its signal processing are basic supportive factors of intelligent transportation system. Because of rapid progress in modern communication engineering, direct digital synthesizer (DDS) is widely used in communications system. However, traditional DDS technology is encountering...

Fuzzy relations are simple mathematical structures that enable a very general representation of fuzzy knowledge, and fuzzy relational calculus offers a powerful machinery for approximate reasoning. However, one of the most relevant limitations of approximate reasoning is the efficiency bottleneck. In...

Interval cooperative game is a kind of model focusing on how to distribute the profit reasonably when payoffs of any alliance are interval numbers. In recent years, the existence and reasonableness of its solution have aroused widespread concern. In this paper, based on the conceptual analyses of various...

How can we deal with the increasing scale of large logistics network for the booming economy? The structure, mechanisms and principles upon the logistics network show an evolutionary tendency which is complex, and interesting for designing and optimizing logistics network. The adaptability, stability...

In this paper, a survey for Data Mining frame work has been done for proposing Data Mining methodologies to engineering materials design applications. An exhaustive literature survey made in this article has covered the modeling systems such as Analytical Model, Numerical Simulation Model and Computer...

An autoregressive moving average (ARMA) is a time series model that is applied in everyday life for pattern recognition and forecasting. The ARMA model contains a noise which is assumed to have a specific distribution. The noise is often considered to have a Gaussian distribution. However in applications,...

This study proposed a new efficient method to investigate tracked vehicle gear transmission system dynamics applying Finite element theory and multi-body dynamics. Torsional excitation was simulated based on an engine dynamic model by considering flexibility of crankshaft, maximum fire pressure and variable...

The ability in providing result that is consistent with actual ranking remains the major concern in group decision making environment. The main aim of this paper is to introduce a novel modification of TOPSIS method to facilitate multi criteria decision making problems based on the concept of Z-numbers...

Real-time DBMS (DataBase Management Systems) are an appropriate storage system under real-time constraints. However real-time DBMS do not implement inference or reasoning mechanisms. Ontologies on the other hand allow these mechanisms by creating formal representations of concepts, properties and relationships...

Knowledge granulation as proposed by Zadeh consists in making objects under discussion into classes called granules; objects within a granule are similar one to another to a satisfactory degree relative to a chosen similarity measure. Rough mereology as developed by Polkowski in a series of works is...

The aim of this paper is to investigate the multiple attribute group decision making(MAGDM) problems with 2-tuple linguistic assessment information, in which the information about attribute weights is incompletely known, and the attribute values take the form of linguistic assessment information. In...

In order to process the linguistic-valued information with uncertainty in the financial decision- making, the present work uses a lattice-valued logical algebra - lattice implication algebra to deal with both comparable and incomparable linguistic truth-values. A new personal financial decision auxiliary...

Supplier evaluation and selection is a kind of problem which includes multiple criteria of qualitative and quantitative properties. From different alternatives it requires to find the best option using different criteria and opinions of the decision makers. Because of the judgments or the bias of the...

A new approach for testing fuzzy hypotheses based on fuzzy data is introduced. According to the proposed approach, a method is first developed based on the defined fuzzy point estimation, which are then used to make a procedure for testing fuzzy hypotheses. This approach has been used to test simple,...

The Quality of Service (QoS) offered by a network is based on criteria such as delay, jitter and message loss. QoS management is crucial to ensure that the network respects the communication constraints defined by the application requirements. The network must dynamically manage QoS according to the...

MEMS gyroscope performs as a sort of sensor to detect angular velocity, with diverse applications in engineering including vehicle and intelligent traffic etc. A balanced vibration of driving module excited by electrostatic driving signal is the base MEMS gyroscope's performance. In order to analyze...

Healthcare waste (HCW) management has become a major environmental and public-health concern especially in developing countries, and therefore, it has been receiving increasing attention from both industrial practitioners and researcher in recent years. Selection of the optimal treatment technology for...

To address the inter-hospital hierarchical allocation and scheduling problems, this research used the pooling resource concept to allocate medical staff among hospital branches as well as determine their monthly schedules. This study proposed a two-stage strategy. The first stage proposed three heuristic...

In this paper, an immune inspired multi-objective fuzzy modeling (IMOFM) mechanism is proposed specifically for high-dimensional regression problems. For such problems, prediction accuracy is often the paramount requirement. With such a requirement in mind, however, one should also put considerable efforts...

Project monitoring and control by using key performance indicators has become a widespread method for decision-making in project-oriented organizations. However, the current schools and IT tools created for this purpose require an upgrade in design due to imprecision, vagueness or uncertainty present...

The tolerance allocation problem has been studied in the literature for decades, usually using mathematical programming (or) heuristic optimization approaches. Elegant tools for minimum cost tolerance allocation have been developed over several decades but still there is no specified tool to find the...

The purpose of this paper is to develop an integrated similarity measures model based on intuitionistic fuzzy sets. This integrated model has improved two similarity measures methods: (1) Ye (, 53, 91-97 (2011)) presented a novel cosine similarity measures method for handling pattern recognition problems...

Differential Evolution (DE) has been applied to many scientific and engineering problems for its simplicity and efficiency. However, the standard DE cannot be used in a binary search space directly. This paper proposes an adaptive binary Differential Evolution algorithm, or ABDE, that has a similar framework...

We provide a methodology to perform an extensive and systematized analysis of problems where experts voice their opinions on the attributes of projects through a hesitant fuzzy decision matrix. This provides the decision-maker with ample information on which he or she can rely in order to make the final...

In this paper, a computer aided system for designing nonwoven materials is presented. As an original approach in the field of nonwoven research, both quality measurement analysis and human knowledge processing are integrated in the system. It allows designers to optimize the structure of nonwoven materials...

Mechanical loading equipments are wildly used in transportation system. Positioning precision is one of the basic functions of machine tools, and structure design is the key to ensuring accuracy. According to the assembly process of tubular-structure, the paper analyzes motion modes to achieve tubular-structure...

The study proposes a comprehensive and systematic approach for multi-criteria and multi-stage facility location selection problem. To handle with high and more uncertainty in the evaluation and selection processes, the problem is solved by using multi-criteria decision making technique with interval...

Workflow systems are commonly used in industry, commerce and government. They provide computerized support for owners of repetitive, highly standardized business processes, with a means of controlling the execution of instances of those processes according to predefined process templates. However, many...

The data-intensive service provision is characterized by the large of scale of services and data and also the high-dimensions of QoS. However, most of the existing works failed to take into account the characteristics of data-intensive services and the effect of the big data sets on the whole performance...

Development of fuzzy if- then rules and formation of membership functions are the important consideration in designing a fuzzy classifier system. This paper presents a Modified Genetic Algorithm (ModGA) approach to obtain the optimal rule set and the membership function for a fuzzy classifier. In the...

With the development of social networking big data, social network group decision-making (SN-GDM) has been widely applied in many fields. This paper focuses on three main components: (1) the determination of the decision makers' (DMs) weights based on different social influence; (2) the anti-deception...

Interval-valued dual hesitant fuzzy set (IVDHFS) as an extended structure of hesitant fuzzy set (HFS), interval-valued HFS and dual hesitant fuzzy set (DHFS) has been developed and applied in multi-attribute decision-making (MADM) problem. While deciding the membership degree (MD) and nonmembership degree...

The multi-attribute group decision making (MAGDM) problem has received considerable attention in the decision analysis field and fruitful achievements have been reported in the literature. This paper focuses on the MAGDM in which the subjective absolute judgement on alternatives with respect to evaluating...

Ring rolling is a complicated process, in which rolling parameters influence directly the quality of ring. It is a process method with high productivity and few waste of material, widely used in transportation industry including automotive, shipbuilding, aerospace etc. During the rolling process of large-sized...

Decision heuristic strategy can be viewed as one of the most central features of state-of-the-art conflict-driven clause-learning SAT solvers. Variable state independent decaying sum (VSIDS) still is the dominant branching heuristics because of its low cost. VSIDS consists of a rewarding mechanism for...

The stock price shows the character of complex non-linear system, along with changes of internal and external environmental factors in stock market. As a form of artificial intelligence, neural network can fully reveal the complex relationship between investors and price fluctuations. After comparing...

procedures for the calculation of point-defect migration energies in Atomistic Kinetic Monte Carlo (AKMC) simulations, as functions of the Local Atomic Configuration (LAC). Two approaches are considered: the Cluster Expansion (CE) and the Artificial Neural Network (ANN). The first is found to be unpromising...

Transactions with quantitative values are commonly seen in real-world applications. Fuzzy mining algorithms have thus been developed recently to induce linguistic knowledge from quantitative databases. In fuzzy data mining, the membership functions have a critical influence on the final mining results....

A new sliding window scheme is introduced with multiple windows to form the protein data for SVM. Two new tertiary classifiers are introduced; one of them makes use of support vector machines as neurons in neural network architecture and the other tertiary classifier is a granular decision tree based...

The trajectory pattern mining problem has recently attracted much attention due to the rapid development of location-acquisition technologies, and parallel computing essentially provides an alternative method for handling this problem. This study precisely addresses the problem of parallel mining of...

Garment purchasing through the e-shopping platforms has become an important trend for consumers of all parts of the world. More and more e-shopping platforms have proposed recommendation functions to consumers in order to make them to obtain more easily desired products and then increase shopping sales....

With the increased financial market volatility, corporate defaults will suffer from the double impact of the external shocks and internal contagion effects. In the existing stochastic default intensity models, the valuation of sensitivity parameters requires a lot of historical data, however, the limited...

This paper proposes a two stage system based in neural network models to classify ischemia via ECG analysis. Two systems based on artificial neural network (ANN) models have been developed in order to discriminate inferolateral and anteroposterior ischemia from normal electrocardiogram (ECG) and other...

Sequence labeling is a common machine-learning task which not only needs the most likely prediction of label for a local input but also seeks the most suitable annotation for the whole input sequence. So it requires the model that is able to handle both the local spatial features and temporal-dependence...

In recent years, hesitant fuzzy sets (HFSs) and neutrosophic sets (NSs) have become a subject of great interest for researchers and have been widely applied to multi-criteria group decision-making (MCGDM) problems. In this paper, multi-valued neutrosophic sets (MVNSs) are introduced, which allow the...

The probability distribution of duration is a critical input for predicting the potential impact of traffic incidents. Most of the previous duration prediction models are discrete, which divide duration into several intervals. However, sometimes the continuous probability distribution is needed. Therefore...

High utility sequential pattern (HUSP) mining has emerged as a novel topic in data mining, its computational complexity increases compared to frequent sequences mining and high utility itemsets mining. A number of algorithms have been proposed to solve such problem, but they mainly focus on mining HUSP...

In this article assessment of morningness of individuals has been performed using fuzzy reasoning approach. The responses are quantified using fuzzy numbers. Based on experts’ opinion a fuzzy rule-base is prepared. The model is validated by considering responses of some students, selected randomly, and...

Optimization problems can often be simplified to the search for an optimal solution in the feasible search space. Based on the concept of simulating the act of human randomized search, a novel algorithm called seeker optimization algorithm (SOA) for real-parameter optimization is proposed in this paper....

This paper presents a practical collision-free motion planning method for general underactuated robot manipulators. First the dynamic properties of underactuated robot manipulator are analyzed, and then the collision avoidance problem is formulated and solved as a position-based force control problem....

We examine the ARCH-GARCH models for the forecasting of the bond price time series provided by VUB bank and make comparisons the forecast accuracy with the class of RBF neural network models. A limited statistical or computer science theory exists on how to design the architecture of RBF networks for...

The traffic signs transfer trip information to drivers through vectors like words, graphs and numbers. Traffic sign with excessive information often makes the drivers have no time to read and understand, leading to risky driving. It is still a problem of how to clarify the relationship between traffic...

In order to further improve the performance of current genetic algorithms aiming at discovering communities, a local search based genetic algorithm (GALS) is here proposed. The core of GALS is a local search based mutation technique. In order to overcome the drawbacks of traditional mutation methods,...

With the easy availability of image processing and image editing tools, the cases of forgery have been raised in the last few years. Now days it is very difficult for a viewer and judicial authorities to verify authenticate a digital image. Cloning or copy-move technique is widely used as forgery to...

Emotion recognition is of great significance to computational intelligence systems. In order to improve the accuracy of emotion recognition, electroencephalogram (EEG) signals and external physiological (EP) signals are adopted due to their perfect performance in reflecting the slight variations of emotions,...

The main objective of subgroup discovery is to discover interesting and interpretable patterns with respect to a specific property. The use of evolutionary fuzzy systems provides good algorithms to approach this problem. In this sense, NMEEF-SD algorithm –one of the most representative evolutionary...

In this paper, we will present a N-Non-Intersecting-Routing (NNIR) algorithm which is used to reduce the cost of resilient routing in telecommunications problems. Resilient Routing is the connections between two locations in a graph through the use of N completely independent routes. Resilient Routing...

This paper deals with an approach for an automated evaluation of the learners' state of knowledge when learning by doing. This approach is called ODALA for "Ontology-Driven Auto-evaluation for e-Learning Approach". It takes place in the context of Computer Based Human Learning Environment (CBHLE) in...

In practical decision-making, we prefer to characterize the uncertain problems with the hybrid data, which consists of various types of data, e.g., categorical data, numerical dada, interval-valued data and set-valued data. The extended rough sets can deal with single type of data based on specific binary...

This paper suggests a novel method for medical image segmentation using kernel based Atanassov's intuitionistic fuzzy clustering. The widely used fuzzy c means clustering that uses Euclidean distance has many limitations in clustering the regions accurately. To overcome these difficulties, we introduce...

The health system in developed countries is facing a problem of scalability in order to accommodate the increased proportion of the elderly population. Scarce resources cannot be sustained unless innovative technology is considered to provide health care in a more effective way. The Smart Home provides...

Drunk driving is one of the leading causes contributing to traffic crashes. There are numerous issues that need to be resolved with the current method of identifying drunk driving. Driving behavior, with the characteristic of real-time, was extensively researched to identify impaired driving behaviors....

Since the shell of the hazelnuts is very hard, it is necessary to squeeze the slit in the axial direction to facilitate peeling. When the hazelnuts are automatically processed in the industry chain, the axial of the hazelnuts needs to be quickly positioned. In this paper, the sum of projection gradient...

This paper focuses on the investigation of filters of pseudo BCK-algebra and BL-algebra, important and popular generic commutative and non-commutative logical algebras. By characterizing Boolean filter and implicative filter in pseudo BCK-algebra, the essential equivalent relation between these two filters...

Cloud Computing is a utility model that offers everything as a service and supports dynamical resource provisioning and auto-scaling in datacenter. Cloud datacenter must envision resource allocation and reallocation to meet out the unpredictable user demand that touted gains in the model. This impact...

The exponential growth in electronic data over internet have increased the demand of a robust and high quality watermarking method for authentication and copyright protection. In general, the existing digital image watermarking methods embed the binary or gray scale watermark into the host image although...

In this paper, text representation and feature selection strategies for Chinese text classification based on n-grams are discussed. Two steps feature selection strategy is proposed which combines the preprocess within classes with the feature selection among classes. Four different feature selection...

In this paper we propose a new approach for laser-based environment device control systems based on the automatic design of a Fuzzy Rule-Based System for laser pointer detection. The idea is to improve the success rate of the previous approaches decreasing as much as possible the false offs and increasing...

Multi-criteria group decision-making (MCGDM) problems are widespread in real life. However, most existing methods, such as hesitant fuzzy set (HFS), hesitant fuzzy linguistic term set (HFLTS) and inter-valued hesitant fuzzy set (IVHFS) only consider the original evaluation data provided by experts but...

Soft set theory and interval set theory are all mathematical tools for dealing with uncertainties. This paper is devoted to the discussion of soft interval set and its application. The notion of soft interval sets is introduced by combining soft set and interval set. Several operations on soft interval...

The aim of this study is to evaluate the susceptibility of landslides at Klang valley area, Malaysia, using a Geographic Information System (GIS) and remote sensing. Landslide locations were identified in the study area from interpretation of aerial photographs and from field surveys. Topographical and...

The attention of driver traveling along a long straight line of prairie highway is easy to be distracted. In this paper, the correlation of straight line length and driver's attention is studied through laboratory simulation experiment and regression analysis. It can be theoretically concluded that the...

Traditionally, the last step of edge detection algorithms, which is called scaling-evaluation, produces the final output classifying each pixel as edge or nonedge. This last step is usually done based on local evaluation methods. The local evaluation makes this classification based on measures obtained...

In order to solve the problem that traditional short text classification methods do not perform well on short text due to the data sparsity and insufficient semantic features, we propose a short text classification method based on convolutional neural network and semantic extension. Firstly, we propose...

With the overwhelming increase of music, it has become difficult to find music which suits the taste of a listener who is in a certain state of emotion. Focusing on the listener's emotional state, this paper presents an emotion-oriented music recommendation algorithm. First, the listener's similarity...

Recently, Neural Network Language Models have been effectively applied to many types of Natural Language Processing (NLP) tasks. One popular type of tasks is the discovery of semantic and syntactic regularities that support the researchers in building a lexicon. Word embedding representations are notably...

The model proposed in this paper, is a hybridization of fuzzy neural network (FNN) and a functional link neural system for time series data prediction. The TSK-type feedforward fuzzy neural network does not take the full advantage of the use of the fuzzy rule base in accurate input-output mapping and...

We combined measures of resting-state functional magnetic resonance imaging and diffusion tensor imaging (DTI) to investigate alterations of function-structure relationships in patients with early-onset schizophrenia. DTI analysis revealed reduced fractional anisotropy in right frontal white matter....

Simulation platforms play an important role in helping intelligent vehicle research, especially for the research of cooperative driving due to the high cost and risk of the real experiments. In order to ease and bring more convenience for cooperative driving tests, we introduce an intelligent vehicle...

In a wireless network environment accurate and timely estimation or prediction of network traffic has gained much importance in the recent past. The network applications use traffic prediction results to maintain its performance by adopting its behaviors. Network Service provider will use the prediction...

Proficient Economic and Financial planning is critical to the successful and efficient operation of power generating and distributing units. This planning becomes quite facile if the accurate and precise knowledge regarding the required power load is ascertained. This research is an innovative effort...

Based on the statistical analysis of coal occurrence characteristics, and dynamic phenomena of coal and rock in Qianjiaying coal mine, China, an area–local outburst early warning system based on outburst key factors and early warning indicators was constructed. Statistical analysis of anomaly features...

In this paper, we present a linguistic interval 2-tuple representation model and new linguistic interval 2-tuple aggregation operators, i.e., linguistic interval 2-tuple power average (LI2TPA) operator, linguistic interval 2-tuple weighted power average (LI2TWPA) operator and linguistic interval 2-tuple...

In this paper, dynamic behavior of a class of high-order fuzzy cellular neural networks (HFCNNs) with time-varying delays is investigated. Compared with the previous results in the literature, the restrictions are loosed, since we do not assume the boundedness and monotonicity on the activation functions,...

This paper proposes a rule base compression method for fuzzy systems. The method is based on filtration of rules with identical linguistic values for the output that are known as non-monotonic rules. The filtration removes the redundant computations in the fuzzy inference with respect to the crisp values...

Decision making is inherent to mankind, as human beings daily face situations in which they should choose among different alternatives by means of reasoning and mental processes. Many of these decision problems are under uncertain environments with vague and imprecise information. This type of information...

Image segmentation is an important task in image processing. However, no universally accepted quality scheme exists for evaluating the performance of various segmentation algorithms or just different parameterizations of the same algorithm. In this paper, an extension of a fusion-based framework for...