Fuzzy frequency response estimation: a case study for the pH neutralization process is proposed in this paper. A fuzzy c-Means clustering algorithm is used to organize the output experimental data of pH neutralization...
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ISBN:
(纸本)9781467315074
Fuzzy frequency response estimation: a case study for the pH neutralization process is proposed in this paper. A fuzzy c-Means clustering algorithm is used to organize the output experimental data of pH neutralization process into groups based on similarities among the data. Starting from the fuzzy clustering a methodology for identification of the linear sub-models, in terms of transfer function, that represent the pH neutralization process in operation regions is developed and these linear sub-models are organized according to Takagi-Sugeno (TS) fuzzy representation. A fuzzy frequency estimation of pH neutralization process is determined through the frequency response function. The main contribution of this paper is to demonstrate through the proposal of a Theorem, that fuzzy frequency response estimation is a region in the magnitude and phase Bode plots.
Aiming at the particularity of data outliers of soft sensor modeling in complex industrial processes,a new outliers detection method for time series is *** new method combines the traditional density-based clustering ...
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ISBN:
(纸本)9781467397155
Aiming at the particularity of data outliers of soft sensor modeling in complex industrial processes,a new outliers detection method for time series is *** new method combines the traditional density-based clustering algorithm(DBSCAN) with soft sensor modeling *** soft sensor modeling errors are used as the guidance of outliers detection process and replace the traditional manual intervention in the clustering *** the outlier detection is completed as well as the soft sensor modeling is *** experiment shows that the new outliers detection method has good performance.
An unauthorized activity on the network is called network intrusion and device or software application which monitors the network parameters in order to detect such an intrusion is called network intrusion detection s...
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An unauthorized activity on the network is called network intrusion and device or software application which monitors the network parameters in order to detect such an intrusion is called network intrusion detection system (NIDS). With high rise in malicious activities on the internet, it is extremely important for NIDS to quickly and correctly identify any kind of malicious activity on the network. Moreover, the system must refrain from raising false alarms in case of normal usage detected as malicious. This paper proposes use of machine learning classification algorithms - XGBoost and AdaBoost with and without clustering to train a model for NIDS. The models are trained and tested using NSL KDD dataset and the results are an improvement over the previous works related to intrusion detection on the same dataset.
Considering the actuality of current speech recognition and the characteristic of RBF neural network,a noise-robust speech recognition system based on RBF neural network is proposed with the entire-supervised *** the ...
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Considering the actuality of current speech recognition and the characteristic of RBF neural network,a noise-robust speech recognition system based on RBF neural network is proposed with the entire-supervised *** the traditional clustering algorithm is employed,there is a flaw that the node center of hidden layer is always sensitive to the initial value,but if the entire-supervised algorithm is used,the flaw will not turn up,and the classification ability of RBF network will be *** results show that,compared with the traditional clustering algorithm,the entire-supervised algorithm is of higher recognition rate in different SNRs than that of clustering algorithm.
Computer graphics uses computers to study graphic representations,process images,and display generated disciplines,realizing the combination of imagery and real-life graphics in people's subjective *** decades of ...
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Computer graphics uses computers to study graphic representations,process images,and display generated disciplines,realizing the combination of imagery and real-life graphics in people's subjective *** decades of development,various kinds of computer graphics and image processing software have come into being,providing people with a lot of convenience for subjective processing and operation,and have been widely used in many *** deepening of the industrialized development process has prompted the rise of the computer core graphic image processing technology *** technology has emerged at the end of the last *** the in-depth development of the industrialization process in the world,its great vitality and vitality continue to show and stand out.
In order to enhance the processing capacity of the inconsistent ordered study information system and transform the rough set of different precision dominance relation, they can enhance the adaptability of inconsistent...
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ISBN:
(纸本)9781510803084
In order to enhance the processing capacity of the inconsistent ordered study information system and transform the rough set of different precision dominance relation, they can enhance the adaptability of inconsistent information by introducing the clustering algorithm, because rough set can effectively deal with imprecise, inconsistent and incomplete information, it can effectively get rid of dependence on a priori knowledge in the learning process, and has strong ability of independent learning. Through the simulation analysis, we found that the autonomous learning method has higher inconsistency ordered information system with the prominent advantages. In the number of different rough set, this method has different accuracy and can be very good to adapt to the change of the offensive and defensive line as well as automatic planning prevention path, which provide the theory reference for the study of basketball training autonomous learning.
Recent advances in proteomic technologies have enabled high-throughput binary data on protein-protein interactions of E. coli to be released into public domain, and many protein complexes have been identified by exper...
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ISBN:
(纸本)9781467368001
Recent advances in proteomic technologies have enabled high-throughput binary data on protein-protein interactions of E. coli to be released into public domain, and many protein complexes have been identified by experimental methods. Although it has a long study history, a large-scale analysis of protein complex in binary PPI network of E. coli is still absent. We used a novel link clustering algorithm named ELPA to infer protein complexes and functional modules in E. coli PPI network. By mapping our results to 276 gold standard protein complexes and protein function annotations offered by EcoCyc, we found that 80.2% of predicted modules mapping well with one or more complexes, while 92.8% of predicted modules tally well with certain GO terms. Furthermore, we compare our results with MCL algorithm, and evaluated our results with several accuracy measures and biological relevance, the result shows that ELPA achieved an average 18.3% improvement over MCL based on the accuracy measures, which means our method will contributes to uncover the complexes of Ecoli.
This paper proposes a robust Criticality-based clustering algorithm (CCA) for Vehicular Ad Hoc NETworks (VANETs) based on the concept of network criticality. Network criticality is a global metric on an undirected gra...
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ISBN:
(纸本)9781457720529
This paper proposes a robust Criticality-based clustering algorithm (CCA) for Vehicular Ad Hoc NETworks (VANETs) based on the concept of network criticality. Network criticality is a global metric on an undirected graph, that quantifies the robustness of the graph against environmental changes such as topology. In this paper, we localize the notion of network criticality and apply it to control cluster formation in the vehicular wireless network. We use the localized notion of node criticality together with a universal link measure, Link Expiration Time (LET), to derive a distributed multi-hop clustering algorithm for VANETs. Simulation results show that the proposed CCA forms robust cluster structures.
Layout is an important issue in designing sensor *** paper brings a new idea for the positioning of nodes in a wireless sensor *** sensors communicate with each other to transmit their data to a high energy communicat...
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Layout is an important issue in designing sensor *** paper brings a new idea for the positioning of nodes in a wireless sensor *** sensors communicate with each other to transmit their data to a high energy communication node which acts as an interface between data processing unit and *** of sensor locations is essential to provide communication for a longer *** energy efficient layout with good coverage based on Genetic algorithm is proposed *** the process of optimization,sensors move to form a uniformly distributed *** two objectives taken into consideration are coverage and *** a set of network layouts are *** simulation results also exhibit improvement of performance with increase in number of generations in the algorithm.
The aim of this study was to use the geographical information system (GIS) to visualize the dengue incidences on a weekly basis in Selangor, Malaysia. Along with the prediction modeling on data using centroid model an...
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ISBN:
(纸本)9781509008469
The aim of this study was to use the geographical information system (GIS) to visualize the dengue incidences on a weekly basis in Selangor, Malaysia. Along with the prediction modeling on data using centroid model and distribution model based on K-means and Expectation Maximization (EM) algorithms respectively. The results show that weekly hotspot were mainly concentrated in the central part of Petaling district of Selangor. R-GIS(R software) and clustering algorithm were used for year 2014 with several weeks to develop the relation between the visualization and prediction of reported incidences. The results are validated for a small region (Petaling district of Selangor state) in Malaysia and they showed vulnerability hotspot in visualizing the dengue incidences. Thus, the proposed method is able to localize the nature of dengue incidence which can further be utilized for vector disease controlled process.
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