@article{ author = {}, title = {A novel algorithm in thresholding, clustering and precise centroiding of night sky stars images}, abstract ={In this paper a novel night sky star pattern recognition and precise centroiding approaches are proposed. Precision and computation time of image processing algorithm paly a great role in spacecraft in which the night sky star images are utilized for attitude determination. Star pattern recognition and centroiding are the most important steps of image processing algorithm in such attitude determination techniques. Here, in order to improve the computation time and precision of the image processing algorithm, a novel star pattern recognition approach including thresholding and clustering steps and precise centroiding method are proposed. Implementation results indicate that the proposed thresholding approach performs better than traditional approaches in dealing with images with uneven illumination. Lower computational burden and average centroiding error of less than 0.045 pixel obtained from experimenting 100 test simulated images, show the great capability of proposed image processing algorithm.}, Keywords = {Centroiding, Converting to binary, Night sky stars images, Spacecraft, Thresholding. }, volume = {11}, Number = {1}, pages = {3-18}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-131-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-131-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2014} } @article{ author = {Khamechian, M.-B. and Saadatmand-Tarzjan, M.}, title = {Segmentation of Endocardium Boundary of the Left Ventricle in Inhomogeneous Cardiac Magnetic Resonance Images}, abstract ={The stochastic active contour scheme (STACS) is a well-known and frequently-used approach for segmentation of the endocardium boundary in cardiac magnetic resonance (CMR) images. However, it suffers significant difficulties with image inhomogeneity due to using a region-based term based on the global Gaussian probability density functions of the innerouter regions of the active contour. On the other hand, the local binary fitting (LBF) provides suitable results for segmentation of inhomogeneous regions because of employing a local Gaussian kernel function.In this paper, we propose a new active contour for inhomogeneous CMR images segmentation by substituting the region-based term of STACS with the corresponding energy functional of LBF.Furthermore, we automatically adjust weighting coefficients of the proposed energy functional according to the simulated annealing algorithm. The performance of the proposed method has been demonstrated on fourteen CMR images. All benchmark images are selected at the end of diastolicsystolic phase of the cardiac cycle. Furthermore, for each benchmark CMR image, the desired boundary was delineated by an expert. Experimental results demonstrated that compared to the geometric active contour, active contour without edge and STACS the proposed method provides significantly superior performance for segmentation of the endocardium boundary of left ventricle of the human heart.}, Keywords = {Segmentation, Cardiac Magnetic Resonance Images, Endocardium Boundary, Geometric Active contour, Level Set, Stochastic Active Contour Scheme, Local Binary Fitting.}, volume = {11}, Number = {1}, pages = {19-31}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-162-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-162-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2014} } @article{ author = {pourmasoomi, asef and kahani, mohsen and Toosi, Seyyed Ahmad and Estiri, Ahm}, title = {Ijaz: An Operational system for single-document summarization of Persian news texts}, abstract ={The rapid growth of published documents on the web has created some new requests for processing, classification and information retrieval. So, the use of natural language processing tools has increased around the world. Automatic summarization known as the core of a wide range of text-processing tools such as decision systems, accountability systems, search engines, etc. And always has been investigated as an important issue in computer science.This paper has introduced "Ijaz", a text summarization system, for Persian documents. For this, we first review the related works in this field, especially for Persian text summarization. We then investigate the using of some new effective features for improvement of the proposed summarizer system. Also for the first time, by using of a large corpus and standardized assessment tools, the proposed method has been evaluated and compared with other existing approaches for Persian text. The results of this evaluations are remarkable.}, Keywords = {Persian Language Processing, Automated Single Document Summarizer, News Text}, volume = {11}, Number = {1}, pages = {33-48}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-134-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-134-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2014} } @article{ author = {Ghasemzadeh, Mohammad and Hessampour, Karim}, title = {Smart Feature Selection for Automatic Modulation recognition using Genetic Programming and Multi-Layer Perceptron Neural Network}, abstract ={This paper shows how we can make advantage of using genetic programming in selection of suitable features for automatic modulation recognition. Automatic modulation recognition is one of the essential components of modern receivers. In this regard, selection of suitable features may significantly affect the performance of the process. In this research we implemented our model by using appropriate software and hardware platforms. Simulations were conducted with 5db and 10db SNRs. We generated test and training data from real ones recorded in an actual communication system. For performance analysis of the proposed method a set of experiments were conducted considering signals with 2ASK, 4ASK, 2PSK, 4PSK, 2FSK and 4FSK modulations. The results show that the selected features by the suggested model improve the performance of automatic modulation recognition considerably. During our experiments we also reached the optimum values and forms for mutation and crossover ratio, elitism policy, fitness function as well as other parameters for the proposed model.}, Keywords = {Feature Selection, Modulation recognition, Genetic Programming, Neural Network.}, volume = {11}, Number = {1}, pages = {49-58}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-115-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-115-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2014} } @article{ author = {mirloo, mahsa and ebrahimnezhad, hossei}, title = {Semantic Segmentation of 3D Model Objects based on Salient Points and Core Extraction}, abstract ={3D model segmentation has an important role in 3D model processing programs such as retrieval, compression and watermarking. In this paper, a new 3D model segmentation algorithm is proposed. Cognitive science research introduces 3D object decomposition as a way of object analysis and detection with human. There are two general types of segments which are obtained from decomposition based on this principle: a core and salient parts. In this approach we start with calculating center of the model. Then, a point with maximum Euclidean distance from the center which represents a prominent part is chosen as the first salient point and its geodesic neighborhood points are deleted from salient point’s search domain. This process is continued until all salient points are detected. Then, the core part which connects the other parts to each other is detected. Thus, 3D model segmentation is completed. Considering center of the model as the reference point and utilizing both Euclidean and geodesic distance and deleting salient point’s neighborhood from salient point’s search domain led our proposed approach to be invariant against translation, rotation and pose changes and also decrease operation time of the proposed algorithm in comparison with the other 3D model segmentation algorithms.}, Keywords = {Segmentation, 3D models, Geodesic Distance, Salient Points, core}, volume = {11}, Number = {1}, pages = {59-72}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-189-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-189-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2014} } @article{ author = {Minaei-Bidgoli, Behrouz}, title = {Extracting person names using name candidate injection in a conditional random field model for Arabic language}, abstract ={Named Entity Recognition and Extraction are very important tasks for discovering proper names including persons, locations, date, and time, inside electronic textual resources. Accurate named entity recognition system is an essential utility to resolve fundamental problems in question answering systems, summary extraction, information retrieval and extraction, machine translation, video interpretation and semantic query expansion. Furthermore, named entity recognition can help us in some state-of-art problems such as removing ambiguity between two common names in different fields, finding out citations in scientific articles, recognizing the associations among persons and improving the results of a search engine to search queries containing named entities. Recently, many researches have been done on named entity recognition for English and other European languages which have led to efficient results whereas the results are not convincing in Arabic, Persian and many of South Asian languages. One of the most necessary and problematic sub-tasks of named entity recognition is the person named extraction. In this article we have introduced a system for person named extraction in Arabic religious texts using "Proper Name candidate injection" by means of Conditional Random Field (CRF) method. Additionally, we have constructed a new corpus from traditional Arabic religious texts. Applying this method, our experiments have significantly achieved more efficient results.}, Keywords = {Name entity recognition, Machine learning, Conditional Random Fields, Persian language, Arabic language }, volume = {11}, Number = {1}, pages = {73-85}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-111-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-111-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2014} } @article{ author = {}, title = {Sonority Sequencing Principle in Persian Language}, abstract ={In this study the distribution of sonority in syllable structure of Persian language is investigated. According to Sonority Sequencing Principle (SSP) sonority is minimum at the Onset, increases to maximum at the nucleus and decreases to last consonant of Coda. The results show that with some exceptions Persian language generally obeys SSP. The results also show that sonorant consonants are occurred more than they were expected no matter where their positions where. Non-sonorants such as plosives occur as expected in pre-vocal contexts which supports the idea that Perceptual Cue Salience plays an important role in shaping sonority sequencing in syllables. The results support the Licensing by Cue hypothesis.}, Keywords = {Sonority Sequencing Principle, Syllable, Persian language, Phonology}, volume = {11}, Number = {1}, pages = {87-94}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-24-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-24-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2014} } @article{ author = {}, title = {Facial expression recognition through the face clustering based discriminant analysis}, abstract ={Improvement of Facial expression recognition is aim of proposed method. This is a new formulation to the linear discriminant analysis. In the new formulation within-class and between-class covariance matrix are estimated on the each cluster and in the test phase new samples are mapped to the subspace that is related to the cluster of them. At the first we addressed clustering analysis of faces and three criteria are proposed for clustering of them. Then cluster based discriminant analysis is achieved through the each three clustering approach. Results show that recognition rate is increased by this new approach and the best result is related to clustering based on the facial index that performance of basic system increased from 95.75% to 98.66%. This is an efficient technique to encounter to large scale dataset in facial expression recognition filed}, Keywords = {Face clustering, Expression recognition, clustering based discriminant analysis }, volume = {11}, Number = {1}, pages = {95-106}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-92-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-92-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2014} } @article{ author = {Shirvani, parisa and VatankhahKhouzani, Mehrdad and yaghmaie, khashayar}, title = {Persian Text Recognition using n-gram Language Models and Grammatical Refinement}, abstract ={Abstract Text recognition has been one of the growing research topics in recent years. Many of these researches have focused on recognition of letters and sub-words as a basis for identifying larger text structures such as words, phrases and sentences. This thesis presents a new method in which the recognized sub-words are combined in order to provide meaningful words and sentences in Farsi texts. Since there may be more than one meaningful combination, the potential meaningful sentences are filtered using Farsi grammatical rules. In the sub-word recognition stage, a double scan method is exploited while the words are extracted using a database of frequent Farsi words. In the last stage a 2 and 3-gram method as well as Farsi grammatical rules are employed to identify the most meaningful sentence from all potential candidates. Experiments have proved the accuracy of the exploited method to be more than 85 percent. Keywords: Text recognition, Persian, Persian language modeling, Natural language processing}, Keywords = {Text recognition, Persian, Persian language modeling, Natural language processing }, volume = {11}, Number = {1}, pages = {107-115}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-135-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-135-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2014} } @article{ author = {gharaee, hossein and aghamoheidin, mahs}, title = {Design of Multi Criteria decision making model for improve Ranking of Information Security risks}, abstract ={One of the most important capabilities of information security management systems, which must be implemented in all organizations according to their requirements, is information security risk management. The application of information security risk management is so important that it can be named as the heart of information security management systems. Information security risk rating is considered as the key part of the risk assessment phase in the process of this management. This article presents an applied method by combining two MADM methods of AHP and TOPSIS in a fuzzy environment in order to improve information security risk rating. The results of comparison between the implementation of the combined FAHP-TOPSIS and the FAHP indicated that the weights presented by the proposed FAHP-TOPSIS model have lower variation coefficients and higher mean compared to the FAHP model. As a result, it provides more accurate results with less percentage error.}, Keywords = {Risk management, Information security, multi criteria decision making models, Analytical Hierarchical process model, TOPSIS model. }, volume = {11}, Number = {2}, pages = {3-14}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-161-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-161-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2015} } @article{ author = {mahloojifar, ali}, title = {Classification of Parkinson Disease Based on Inter - and Intra -Regional Biomarkers of the Brain Motor Network Using Resting State fMRI Data}, abstract ={Parkinson’s disease (PD) is a progressive neurological disorder characterized by tremor, rigidity, and slowness of movement. Recent studies on investigation of the brain function show that there are spontaneous fluctuations between regions at rest as resting state network affected in various disorders. In this paper, we used amplitude of low frequency fluctuation (ALFF) for the study of intra-regional characteristics and cross-correlation analysis for the relationship between anatomical regions. According to the results of CCA, we presented functional connectivity network in healthy and PD. Comparing two networks showed that, firstly the activity of cerebellum and basal ganglia areas had a significant negative correlation in PD patients, while this relationship is weak and non-significant in healthy. We also used mean values of ALFF and ReHo as intra-region biomarkers in addition with inter-region characteristics in discriminative analysis to classify PD from healthy. This showed 85% accuracy in clustering. In addition, the score index is 89% and Jaccard coefficient of this clustering is 75%. We found that inter-regional feature (CCA) was more significant compared to the intra-regional feature (ALFF) and functional connectivity between left cerebellum and left putamen was the best discriminator between PD and control}, Keywords = {functional Magnetic Resonance Imaging (fMRI), Functional connectivity, Resting State, Parkinson Disease, Amplitude of Low Frequency Fluctuations(ALFF), Regional Homogeneity(ReHo), Cross Correlation Analysis(CCA) }, volume = {11}, Number = {2}, pages = {15-29}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-105-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-105-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2015} } @article{ author = {Hajebi, Pooya and AlModarresi, Seyed Mohammad Taghi}, title = {Improvement of Networked Control Systems Performance Using Rotation in Fuzzy Logic Controller Rules}, abstract ={This paper addresses a novel control method adapted with varying time delay to improve NCS performance. A well-known challenge with NCSs is the stochastic time delay. Conventional controllers such as PID type controllers which are just tuned with a constant time delay could not be a solution for these systems. Fuzzy logic controllers due to their nonlinear characteristic which is compatible with these systems are potentially a wise option for their control purpose. Fuzzy logic controller could become adaptive by means of neural networks and beneficial to deal with the varying time delay problem. This novel method suggests an adaptive fuzzy logic controller which has been controlled and adapted through the neural network. The rule-based table of designed fuzzy logic controller rotates in relation to estimated time delay. The amount of rotation is obtained from neural network. The proposed method follows the input easily, despite classical methods which result in an unstable system especially over the large time delays as large as 600 ms.}, Keywords = {Adaptive Fuzzy Logic Controller, Data Communication Networks, Fuzzy Rule-Table Rotation, Networked Control Systems, Neural Networks.}, volume = {11}, Number = {2}, pages = {31-42}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-205-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-205-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2015} } @article{ author = {Shamsigooshki, Asma and Nezamabadi-pour, Hossein and Saryazdi, Saeed and Kabir, ehsanollah}, title = {a relevance feedback approach based on similarity refinement in content based image retrieval}, abstract ={In content based image retrieval systems, the suitable visual features are extracted from images and stored in the feature database Then the feature database are searched to find the most similar images to the query image. In this paper, three types of visual features by 270 components were used for image indexing. Here, we use a weighted distance for similarity measurement between two images. This paper presents a new relevance feedback approach based on similarity refinement. In the proposed approach, weight correction of feature’s components is done by a proposed rule set using the mean and standard deviation of feature vectors of related (positive) and non-related (negative) images. Also, the weight of each type of features is adjusted according to the related images’ rank in the retrieval with this type of feature. To evaluate the performance of the proposed method, a set of comparative experiments on a general image database containing 10000 images of 82 different semantic groups are performed. The results confirm the efficiency of the proposed method comparing by well-known conventional methods.}, Keywords = {relevance feedback, image retrieval, similarity refinement, query refinement.}, volume = {11}, Number = {2}, pages = {43-55}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-138-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-138-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2015} } @article{ author = {Ghassemian, Mohammad Has}, title = {Spectral and Spatial Unmixing of Hyperspectral Images Using Semi-nonnegative Matrix Factorization and Principal Component Analysis}, abstract ={Unmixing of remote-sensing data using nonnegative matrix factorization has been considered recently. To improve performance, additional constraints are added to the cost function. The main challenge is to introduce constraints that lead to better results for unmixing. Correlation between bands of Hyperspectral images is the problem that is paid less attention to it in the unmixing algorithms. In this paper, we have proposed a new method for unmixing of Hyperspectral data using semi-nonnegative matrix factorization and principal component analysis. In the proposed method, spectral and spatial unmixing is performed simultaneously. Physical constraints applied based on Linear Mixing Model. In addition to physical constraints, characteristics of Hyperspectral data have been exploited in the unmixing process. Sparseness of the abundance is one of the important features of Hyperspectral data, which is applied using the nsNMF matrix. In the proposed method update rules is derived using the ALS algorithm. In the final section of this paper, real and synthetic Hyperspectral data is used to verify the effectiveness of the proposed algorithm. Obtained results show the superiority of the proposed algorithm in comparison with some unmixing algorithms}, Keywords = {Hyperspectral Image, Remote Sensing Data Unmixing, Blind Source Separation, Semi-nonnegative Matrix Factorization, Principal Component Analysis. }, volume = {11}, Number = {2}, pages = {57-70}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-94-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-94-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2015} } @article{ author = {khallash, mojtaba and Minaei-Bidgoli, Behrouz}, title = {Effect of morphologies on Persian dependency parsing}, abstract ={Data-driven systems can be adapted to different languages and domains easily. Using this trend in dependency parsing was lead to introduce data-driven approaches. Existence of appreciate corpora that contain sentences and theirs associated dependency trees are the only pre-requirement in data-driven approaches. Despite obtaining high accurate results for dependency parsing task in English language, for many of other languages with high free-word order and rich morphology, most applying algorithms lead to drop in accuracy compared to English language. Therefore, data-driven systems require careful selection of features and tuning of parameters to reach optimal performance. A dependency corpus for Persian language introduced recently. Persian language has high free-word order and rich morphology. In this paper we try to find detect effective factors for decreasing parsing accuracy and we present solutions to improve the accuracy.}, Keywords = {Dependency Parsing, Morphologically Rich Languages, Morphological Features}, volume = {11}, Number = {2}, pages = {71-80}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-124-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-124-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2015} } @article{ author = {}, title = {Applying Recurrence Plots to Analyze Heart Rate Signals in Experienced Meditators}, abstract ={The current study analyses the dynamics of the heart rate signals during specific psychological states in order to obtain a detailed understanding of the heart rate patterns during meditation. In the proposed approach, we used heart rate time series available in Physionet database. The dynamics of the signals are then analyzed before and during meditation by examining the recurrence quantification analysis. The results show that the measures of recurrence plots are increased significantly during meditation (p<0.05), which indicates that the dimension of signals are decreased during meditation. In general, the results reveal that the heart rate signals of experienced meditators transit from a chaotic, highly-complex behavior before meditation to a low dimensional chaotic (and quasi-periodic) motion during meditation. This can be due to decreased nonlinear interaction of variables in meditation states and may be related to increased parasympathetic activity and increase of relaxation state.}, Keywords = {Chaotic, Heart Rate signals, Meditation, Recurrence Quantification Analysis}, volume = {11}, Number = {2}, pages = {81-90}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-49-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-49-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2015} } @article{ author = {keyvanpour, Mohammadrez}, title = {A Divisive Hierarchical Clustering-based Method for Indexing Image Information}, abstract ={It is conventional to use multi-dimensional indexing structures to accelerate search operations in content-based image retrieval systems. Many efforts have been done in order to develop multi-dimensional indexing structures so far. In most practical applications of image retrieval, high-dimensional feature vectors are required, but current multi-dimensional indexing structures lose their efficiency with growth of dimensions. Increase in dimensions of data space leads to exponentially growth of the search space and increase of the number of nodes in multi-dimensional indexing structure, as well as increase in overlap between nodes in multi-dimensional indexing structures. These problems lead to increase in cost of search through indexing structure and therefore to reduction in efficiency of these structures in high-dimensional spaces. The main goal of this research is to propose a divisive hierarchical clustering-based multi-dimensional indexing structure in order to manage high-dimensional feature vectors extracted from images, which also prevents overlapping in its structure.Various tests and analyses of experimental results on high-dimensional datasets indicate the performance of our proposed method in comparison with others.}, Keywords = {Content-based image retrieval, Multi-dimensional indexing structures, Hierarchical divisive clustering, Projection pursuit methods }, volume = {11}, Number = {2}, pages = {91-109}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-74-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-74-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2015} } @article{ author = {mahdizadeh, mahboubeh and eftekhari, mahdi}, title = {A new fuzzy rules weighting approach based on Genetic Programming for imbalanced classification}, abstract ={In classification problems, we often encounter datasets with different percentage of patterns (i.e. classes with a high pattern percentage and classes with a low pattern percentage). These problems are called “classification Problems with imbalanced data-sets”. Fuzzy rule based classification systems are the most popular fuzzy modeling systems used in pattern classification problems. Rule weights have been usually used to improve the classification accuracy and fuzzy versions of confidence and support merits have been widely used for rules weighting in fuzzy rule based classifiers. In this paper, we propose an evolutionary approach based on genetic programming to generate weighting expressions. For producing expressions confidence, support, lift and recall merits are used as terminals of genetic programming. Experiments are performed over 20 imbalanced KEEL's datasets and the results are analyzed using statistical tests. The results show that the proposed method improves the classification accuracy of FRBCS.}, Keywords = {Imbalanced dataset problems, Fuzzy Rule-Based Classification Systems(FRBCSs), Weighting rules, Genetic Programming}, volume = {11}, Number = {2}, pages = {111-125}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-28-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-28-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2015} }