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61.
Shahla Nemati Mohammad Ehsan Basiri Nasser Ghasem-Aghaee Mehdi Hosseinzadeh Aghdam 《Expert systems with applications》2009,36(10):12086-12094
Protein function prediction is an important problem in functional genomics. Typically, protein sequences are represented by feature vectors. A major problem of protein datasets that increase the complexity of classification models is their large number of features. Feature selection (FS) techniques are used to deal with this high dimensional space of features. In this paper, we propose a novel feature selection algorithm that combines genetic algorithms (GA) and ant colony optimization (ACO) for faster and better search capability. The hybrid algorithm makes use of advantages of both ACO and GA methods. Proposed algorithm is easily implemented and because of use of a simple classifier in that, its computational complexity is very low. The performance of proposed algorithm is compared to the performance of two prominent population-based algorithms, ACO and genetic algorithms. Experimentation is carried out using two challenging biological datasets, involving the hierarchical functional classification of GPCRs and enzymes. The criteria used for comparison are maximizing predictive accuracy, and finding the smallest subset of features. The results of experiments indicate the superiority of proposed algorithm. 相似文献
62.
Building extraction from high-resolution satellite images (HRSI) in urban areas is an intricate problem. Recent studies proposed different methods during 2005–2015. However, in HRSI, they have not investigated the effects of challenges altogether. This paper studies the effects of non-building features which are the main drawbacks in building extraction. To overcome each challenge, it reviews recent strategies between 2005 and 2015. The pros and cons of each strategy are discussed, and proper strategies are combined to generate hybrid methods. Lower cost and fewer strategies are efficient attributes to recognize the best hybrid methods. Hybrid methods can be useful for different case studies in the future. 相似文献
63.
Handling objects with robotic soft fingers without considering the odds of slippage are not realistic. Grasping and manipulation algorithms have to be tested under such conditions for evaluating their robustness. In this paper, a dynamic analysis of rigid object manipulation with slippage control is studied using a two-link finger with soft hemispherical tip. Dependency on contact forces applied by a soft finger while grasping a rigid object is examined experimentally. A power-law model combined with a linear viscous damper is used to model the elastic behavior and damping effect of the soft tip, respectively. In order to obtain precise dynamic equations governing the system, two second-order differential equations with variable coefficients have been designed to describe the different possible states of the contact forces accordingly. A controller is designed based on the rigid fingertip model using the concept of feedback linearization for each phase of the system dynamics. Numerical simulations are used to evaluate the performance of the controller. The results reveal that the designed controller shows acceptable performance for both soft and rigid finger manipulation in reducing and canceling slippage. Furthermore, simulations indicate that the applied force in the soft finger manipulation is considerably less than the rigid “one.”. 相似文献
64.
In this work, we present a scheme which is based on non-staggered grids. This scheme is a new family of non-staggered central schemes for hyperbolic conservation laws. Motivation of this work is a staggered central scheme recently introduced by A.A.I. Peer et al. [A new fourth-order non-oscillatory central scheme for hyperbolic conservation laws, Appl. Numer. Math. 58 (2008) 674–688]. The most important properties of the technique developed in the current paper are simplicity, high-resolution and avoiding the use of staggered grids and hence is simpler to implement in frameworks which involve complex geometries and boundary conditions. Numerical implementation of the new scheme is carried out on the scalar conservation laws with linear, non-linear flux and systems of hyperbolic conservation laws. The numerical results confirm the expected accuracy and high-resolution properties of the scheme. 相似文献
65.
Mehdi Ghatee 《Computer Communications》2011,34(7):835-846
This paper treats with integral multi-commodity flow through a network. To enhance the Quality of Service (QoS) for channels, it is necessary to minimize delay and congestion. Decreasing the end-to-end delay and consumption of bandwidth across channels are dependent and may be considered in very complex mathematical equations. To capture with this problem, a multi-commodity flow model is introduced whose targets are minimizing delay and congestion in one model. The flow through the network such as packets, also needs to get integral values. A model covering these concepts, is NP-hard while it is very important to find transmission strategies in real-time. For this aim, we extend a cooperative algorithm including traditional mathematical programming such as path enumeration and a meta-heuristic algorithm such as genetic algorithm. To find integral solution satisfying demands of nodes, we generalize a hybrid genetic algorithm to assign the integral commodities where they are needed. In this hybrid algorithm, we use feasible encoding and try to keep feasibility of chromosomes over iterations. By considering some random networks, we show that the proposed algorithm yields reasonable results in a few number of iterations. Also, because this algorithm can be applied in a wide range of objective functions in terms of delay and congestion, it is possible to find some routs for each commodity with high QoS. Due to these outcomes, the presented model and algorithm can be utilized in a variety of application in computer networks and transportation systems to decrease the congestion and increase the usage of channels. 相似文献
66.
The Optimal Sequenced Route (OSR) query strives to find a route of minimum length starting from a given source location and passing through a number of typed locations in a specific sequence imposed on the types of the locations. In this paper, we propose a pre-computation approach
to OSR query in both vector and metric spaces. We exploit the geometric properties of the solution space and theoretically
prove its relation to additively weighted Voronoi diagrams. Our approach recursively accesses these diagrams to incrementally build the OSR. Introducing the analogous diagrams for
the space of road networks, we show that our approach is also efficiently applicable to this metric space. Our experimental
results verify that our pre-computation approach outperforms the previous index-based approaches in terms of query response
time.
This research has been funded in part by NSF grants EEC-9529152 (IMSC ERC), IIS-0238560 (PECASE), IIS-0324955 (ITR), IIS-0534761,
and unrestricted cash gifts from Google and Microsoft. Any opinions, findings, and conclusions or recommendations expressed
in this material are those of the author(s) and do not necessarily reflect the views of the NSF.
Mehdi Sharifzadeh received his B.S. and M.S. degrees in Computer Engineering from Sharif University of Technology in Tehran, Iran, in 1995, and 1998, respectively. He received his Ph.D. degree in Computer Science from the University of Southern California in May 2007. His research interests include spatial and spatio-temporal databases, data stream processing, and sensor networks. Cyrus Shahabi is currently an Associate Professor and the Director of the Information Laboratory (InfoLAB) at the Computer Science Department and also a Research Area Director at the NSF’s Integrated Media Systems Center at the University of Southern California. He received his B.S. in Computer Engineering from Sharif University of Technology in 1989 and then his M.S. and Ph.D. degrees in Computer Science from the University of Southern California in May 1993 and August 1996, respectively. He has two books and more than hundred articles, book chapters, and conference papers in the areas of databases, GIS and multimedia. Dr. Shahabi’s current research interests include Geospatial and Multidimensional Data Analysis, Peer-to-Peer Systems and Streaming Architectures. He is currently an associate editor of the IEEE Transactions on Parallel and Distributed Systems and on the editorial board of ACM Computers in Entertainment magazine. He is also a member of the steering committees of IEEE NetDB and general co-chair of ACM GIS 2007. He serves on many conference program committees such as ACM SIGKDD 2006-08, IEEE ICDE 2006 and 08, SSTD 2005-08 and ACM SIGMOD 2004. Dr. Shahabi is the recipient of the 2002 NSF CAREER Award and 2003 Presidential Early Career Awards for Scientists and Engineers. In 2001, he also received an award from the Okawa Foundations. 相似文献
Mehdi Sharifzadeh (Corresponding author)Email: URL: http://infolab.usc.edu |
Cyrus ShahabiEmail: |
Mehdi Sharifzadeh received his B.S. and M.S. degrees in Computer Engineering from Sharif University of Technology in Tehran, Iran, in 1995, and 1998, respectively. He received his Ph.D. degree in Computer Science from the University of Southern California in May 2007. His research interests include spatial and spatio-temporal databases, data stream processing, and sensor networks. Cyrus Shahabi is currently an Associate Professor and the Director of the Information Laboratory (InfoLAB) at the Computer Science Department and also a Research Area Director at the NSF’s Integrated Media Systems Center at the University of Southern California. He received his B.S. in Computer Engineering from Sharif University of Technology in 1989 and then his M.S. and Ph.D. degrees in Computer Science from the University of Southern California in May 1993 and August 1996, respectively. He has two books and more than hundred articles, book chapters, and conference papers in the areas of databases, GIS and multimedia. Dr. Shahabi’s current research interests include Geospatial and Multidimensional Data Analysis, Peer-to-Peer Systems and Streaming Architectures. He is currently an associate editor of the IEEE Transactions on Parallel and Distributed Systems and on the editorial board of ACM Computers in Entertainment magazine. He is also a member of the steering committees of IEEE NetDB and general co-chair of ACM GIS 2007. He serves on many conference program committees such as ACM SIGKDD 2006-08, IEEE ICDE 2006 and 08, SSTD 2005-08 and ACM SIGMOD 2004. Dr. Shahabi is the recipient of the 2002 NSF CAREER Award and 2003 Presidential Early Career Awards for Scientists and Engineers. In 2001, he also received an award from the Okawa Foundations. 相似文献
67.
A Wavelet-ANFIS Hybrid Model for Groundwater Level Forecasting for Different Prediction Periods 总被引:8,自引:2,他引:6
Vahid Moosavi Mehdi Vafakhah Bagher Shirmohammadi Negin Behnia 《Water Resources Management》2013,27(5):1301-1321
Artificial neural network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) have an extensive range of applications in water resources management. Wavelet transformation as a preprocessing approach can improve the ability of a forecasting model by capturing useful information on various resolution levels. The objective of this research is to compare several data-driven models for forecasting groundwater level for different prediction periods. In this study, a number of model structures for Artificial Neural Network (ANN), Adaptive Neuro-Fuzzy Inference System (ANFIS), Wavelet-ANN and Wavelet-ANFIS models have been compared to evaluate their performances to forecast groundwater level with 1, 2, 3 and 4 months ahead under two case studies in two sub-basins. It was demonstrated that wavelet transform can improve accuracy of groundwater level forecasting. It has been also shown that the forecasts made by Wavelet-ANFIS models are more accurate than those by ANN, ANFIS and Wavelet-ANN models. This study confirms that the optimum number of neurons in the hidden layer cannot be always determined by using a specific formula but trial-and-error method. The decomposition level in wavelet transform should be determined according to the periodicity and seasonality of data series. The prediction of these models is more accurate for 1 and 2 months ahead (for example RMSE?=?0.12, E?=?0.93 and R 2?=?0.99 for wavelet-ANFIS model for 1 month ahead) than for 3 and 4 months ahead (for example RMSE?=?2.07, E?=?0.63 and R 2?=?0.91 for wavelet-ANFIS model for 4 months ahead). 相似文献
68.
Mehrdad Kargari Mohammad Mehdi Sepehri 《Expert systems with applications》2012,39(5):4740-4748
Clustering of retail stores in a distribution network with specific geographical limits plays an important and effective role in distribution and transportation costs reduction. In this paper, the relevant data and information for an established automotive spare-parts distribution and after-sales services company (ISACO) for a 3-year period have been analyzed. With respect to the diversity and lot size of the available information such as stores location, order, goods, transportation vehicles and road and traffic information, three effecting factors with specific weights have been defined for the similarity function: 1. Euclidean distance, 2. Lot size 3. Order concurrency. Based on these three factors, the similarity function has been examined through 5 steps using the Association Rules principles, where the clustering of the stores is performed using k-means algorithm and similar stores are allocated to the clusters. These steps include: 1. Similarity function based on the Euclidean distances, 2. Similarity function based on the order concurrency, 3. Similarity function based on the combination of the order concurrency and lot size, 4. Similarity function based on the combination of these three factors and 5. Improved similarity function. The above mentioned clustering operation for each 5 cases addressed in data mining have been carried out using R software and the improved combinational function has been chosen as the optimal clustering function. Then, trend of each retail store have been analyzed using the improved combinational function and along with determining the priority of the depot center establishment for every cluster, the appropriate distribution policies have been formulated for every cluster. The obtained results of this study indicate a significant cost reduction (32%) in automotive spare-parts distribution and transportation costs. 相似文献
69.
In this paper, the problem of robust matrix root‐clustering is addressed. The studied matrices are subject to both polytopic and unstructured uncertainties. An original point is the large choice of clustering regions enabled by the proposed approach since these regions can be unions of possibly disjoint and non‐symmetric subregions of the complex plane. The precise purpose is, considering a specified polytope, to determine the greatest robustness bound on the unstructured uncertainty such that robust matrix root‐clustering is ensured. To reduce conservatism in the derivation of the bound, the reasoning relies on a framework based upon parameter‐dependent Lyapunov functions. The bound value is computed by solving an ?? ?? ? problem. Copyright © 2003 John Wiley & Sons, Ltd. 相似文献
70.
Current remote sensing satellites with multispectral sensors capture high-resolution images and produce vast quantities of data. The size and volume of this information has dramatically increased in the last decade as sensor resolution and capabilities have significantly improved, without a similar improvement on the satellite system capacity to accommodate these changes. Remote sensing satellites currently operate on a “store and forward” paradigm, where data is stored on the satellite until the satellite is in view of the ground station. Low Earth orbit satellites may only see a ground station for a 10–15 min window per pass, in which time all the collected information must be telemetered to the ground. This process requires large and expensive onboard storage resources and places tremendous stress on communication channels. Hence, a complete image may not be successfully telemetered in one pass causing a significant delay between capture and analysis and limiting the benefits of these images. Smart satellites are more technologically advanced, require less ground station support and data storage, and are capable of transmitting required information quickly and easily to ground stations. With onboard reconfigurable data processing, these satellites have faster data product turnaround, less communication requirements, and provide more useful information. The high performance computing (HPC-I) payload on board the Australian satellite FedSat, launched in December 2002, is a demonstration device of the feasibility of reconfigurable computing technology in space. This device is small in size, requires low power, and has the processing capacity to handle large data volumes. Using this device in conjunction with a high-resolution imaging sensor, such as the bispectral infrared detection (BIRD) sensor, smart dedicated satellites become a feasible and cost effective solution to remote sensing needs. This paper elaborates on the system level design of a real-time fire observation system in the context of a smart satellite mission for detecting and monitoring natural disasters. The proposed system is built upon flight tested field programmable gate arrays based HPC-I technology, and would be capable of producing useful information about natural disasters directly broadcasted to interested parties within rapid timeframes. The algorithms for onboard real-time detection of direction, intensity, and location of fires are discussed, and reliable algorithms for detecting and verifying these fires using smoke plume detection are presented. Further work is described including fire-front analysis and the tracking of fire movement. 相似文献