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Yudong Zhang

Bio: Yudong Zhang is an academic researcher from University of Leicester. The author has contributed to research in topics: Computer science & Artificial intelligence. The author has an hindex of 71, co-authored 437 publications receiving 15015 citations. Previous affiliations of Yudong Zhang include Nanjing Audit University & Nanjing University.


Papers
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Journal ArticleDOI
TL;DR: This survey presented a comprehensive investigation of PSO, including its modifications, extensions, and applications to the following eight fields: electrical and electronic engineering, automation control systems, communication theory, operations research, mechanical engineering, fuel and energy, medicine, chemistry, and biology.
Abstract: Particle swarm optimization (PSO) is a heuristic global optimization method, proposed originally by Kennedy and Eberhart in 1995. It is now one of the most commonly used optimization techniques. This survey presented a comprehensive investigation of PSO. On one hand, we provided advances with PSO, including its modifications (including quantum-behaved PSO, bare-bones PSO, chaotic PSO, and fuzzy PSO), population topology (as fully connected, von Neumann, ring, star, random, etc.), hybridization (with genetic algorithm, simulated annealing, Tabu search, artificial immune system, ant colony algorithm, artificial bee colony, differential evolution, harmonic search, and biogeography-based optimization), extensions (to multiobjective, constrained, discrete, and binary optimization), theoretical analysis (parameter selection and tuning, and convergence analysis), and parallel implementation (in multicore, multiprocessor, GPU, and cloud computing forms). On the other hand, we offered a survey on applications of PSO to the following eight fields: electrical and electronic engineering, automation control systems, communication theory, operations research, mechanical engineering, fuel and energy, medicine, chemistry, and biology. It is hoped that this survey would be beneficial for the researchers studying PSO algorithms.

836 citations

Journal ArticleDOI
TL;DR: An improved bacterial chemotaxis optimization (IBCO) is proposed, which is then integrated into the back propagation (BP) artificial neural network to develop an efficient forecasting model for prediction of various stock indices.
Abstract: The paper proposed an improved bacterial chemotaxis optimization (IBCO), which is then integrated into the back propagation (BP) artificial neural network to develop an efficient forecasting model for prediction of various stock indices. Experiments show its better performance than other methods in learning ability and generalization.

414 citations

Journal ArticleDOI
TL;DR: A novel spam detection method that focused on reducing the false positive error of mislabeling nonspam as spam, which demonstrated the MBPSO is superior to GA, RSA, PSO, and BPSO in terms of classification performance and wrappers are more effective than filters with regard to classification performance indexes.
Abstract: In this paper, we proposed a novel spam detection method that focused on reducing the false positive error of mislabeling nonspam as spam. First, we used the wrapper-based feature selection method to extract crucial features. Second, the decision tree was chosen as the classifier model with C4.5 as the training algorithm. Third, the cost matrix was introduced to give different weights to two error types, i.e., the false positive and the false negative errors. We define the weight parameter as a to adjust the relative importance of the two error types. Fourth, K-fold cross validation was employed to reduce out-of-sample error. Finally, the binary PSO with mutation operator (MBPSO) was used as the subset search strategy. Our experimental dataset contains 6000 emails, which were collected during the year of 2012. We conducted a Kolmogorov–Smirnov hypothesis test on the capital-run-length related features and found that all the p values were less than 0.001. Afterwards, we found a = 7 was the most appropriate in our model. Among seven meta-heuristic algorithms, we demonstrated the MBPSO is superior to GA, RSA, PSO, and BPSO in terms of classification performance. The sensitivity, specificity, and accuracy of the decision tree with feature selection by MBPSO were 91.02%, 97.51%, and 94.27%, respectively. We also compared the MBPSO with conventional feature selection methods such as SFS and SBS. The results showed that the MBPSO performs better than SFS and SBS. We also demonstrated that wrappers are more effective than filters with regard to classification performance indexes. It was clearly shown that the proposed method is effective, and it can reduce the false positive error without compromising the sensitivity and accuracy values.

372 citations

Journal ArticleDOI
Bing Wu1, Dayong Zhao1, Haiying Jia1, Yudong Zhang1, Xu-Xiang Zhang1, S. P. Cheng1 
TL;DR: In order to investigate the contamination levels of trace metals, surface water samples were collected from six regions along Yangtze River in Nanjing Section and Hazard Quotients of all metals were lower than unity, except As and Cd, suggesting that those two metals have potential adverse effects on local residents.
Abstract: In order to investigate the contamination levels of trace metals, surface water samples were collected from six regions along Yangtze River in Nanjing Section. The concentrations of trace metals (As, B, Ba, Be, Cd, Cr, Cu, Fe, Pb, Li, Mn, Mo, Ni, Sb, Se, Sn, Sr, V and Zn) were determined using inductively coupled plasma-atomic emission spectrometry (ICP-AES). Total concentrations of the metals in the water samples ranged from 825.1 to 950.4 μg/L. The result was compared with international water quality guidelines. Seven metals levels were above the permissible limit as prescribed by guidelines. A preliminary risk assessment was then carried out to determine the human health risk via calculating Hazard Quotient and carcinogenic risk of the metals. Hazard Quotients of all metals were lower than unity, except As. The carcinogenic risk of As and Cd was higher than 10−6, suggesting that those two metals have potential adverse effects on local residents.

321 citations

Journal ArticleDOI
TL;DR: This paper presents a neural network (NN) based method to classify a given MR brain image as normal or abnormal, which first employs wavelet transform to extract features from images, and then applies the technique of principle component analysis (PCA) to reduce the dimensions of features.
Abstract: Automated and accurate classification of MR brain images is of importance for the analysis and interpretation of these images and many methods have been proposed. In this paper, we present a neural network (NN) based method to classify a given MR brain image as normal or abnormal. This method first employs wavelet transform to extract features from images, and then applies the technique of principle component analysis (PCA) to reduce the dimensions of features. The reduced features are sent to a back propagation (BP) NN, with which scaled conjugate gradient (SCG) is adopted to find the optimal weights of the NN. We applied this method on 66 images (18 normal, 48 abnormal). The classification accuracies on both training and test images are 100%, and the computation time per image is only 0.0451s.

318 citations


Cited by
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Christopher M. Bishop1
01 Jan 2006
TL;DR: Probability distributions of linear models for regression and classification are given in this article, along with a discussion of combining models and combining models in the context of machine learning and classification.
Abstract: Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

10,141 citations

Book
31 Jul 1997
TL;DR: This book explores the meta-heuristics approach called tabu search, which is dramatically changing the authors' ability to solve a host of problems that stretch over the realms of resource planning, telecommunications, VLSI design, financial analysis, scheduling, spaceplanning, energy distribution, molecular engineering, logistics, pattern classification, flexible manufacturing, waste management,mineral exploration, biomedical analysis, environmental conservation and scores of other problems.
Abstract: From the Publisher: This book explores the meta-heuristics approach called tabu search, which is dramatically changing our ability to solve a hostof problems that stretch over the realms of resource planning,telecommunications, VLSI design, financial analysis, scheduling, spaceplanning, energy distribution, molecular engineering, logistics,pattern classification, flexible manufacturing, waste management,mineral exploration, biomedical analysis, environmental conservationand scores of other problems. The major ideas of tabu search arepresented with examples that show their relevance to multipleapplications. Numerous illustrations and diagrams are used to clarifyprinciples that deserve emphasis, and that have not always been wellunderstood or applied. The book's goal is to provide ''hands-on' knowledge and insight alike, rather than to focus exclusively eitheron computational recipes or on abstract themes. This book is designedto be useful and accessible to researchers and practitioners inmanagement science, industrial engineering, economics, and computerscience. It can appropriately be used as a textbook in a masterscourse or in a doctoral seminar. Because of its emphasis on presentingideas through illustrations and diagrams, and on identifyingassociated practical applications, it can also be used as asupplementary text in upper division undergraduate courses. Finally, there are many more applications of tabu search than canpossibly be covered in a single book, and new ones are emerging everyday. The book's goal is to provide a grounding in the essential ideasof tabu search that will allow readers to create successfulapplications of their own. Along with the essentialideas,understanding of advanced issues is provided, enabling researchers togo beyond today's developments and create the methods of tomorrow.

6,373 citations

Journal Article
TL;DR: It is hypothesized that beta oscillations and/or coupling in the beta-band are expressed more strongly if the maintenance of the status quo is intended or predicted, than if a change is expected.
Abstract: In this review, we consider the potential functional role of beta-band oscillations, which at present is not yet well understood. We discuss evidence from recent studies on top-down mechanisms involved in cognitive processing, on the motor system and on the pathophysiology of movement disorders that suggest a unifying hypothesis: beta-band activity seems related to the maintenance of the current sensorimotor or cognitive state. We hypothesize that beta oscillations and/or coupling in the beta-band are expressed more strongly if the maintenance of the status quo is intended or predicted, than if a change is expected. Moreover, we suggest that pathological enhancement of beta-band activity is likely to result in an abnormal persistence of the status quo and a deterioration of flexible behavioural and cognitive control.

1,837 citations