Distributed computational intelligence applied in bioinformatics
Distributed computational intelligence applied in bioinformatics
... work in the area of computational intelligence also grows rapidly Computational Intelligence (CI) is an area of fundamental and applied research involving numerical information processing (in contrast ... The traditional searching methods are very troublesome and time-consuming This project brings the new engineering insight into the bioinformatics field, making the searching more effective and ... discussed in chapter Conclusions are drawn in chapter Chapter Distributed Computational Intelligence Technique 2.1 Introduction With the rapidly growing demand for new software systems having increasing...
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Computational intelligence techniques in visual pattern recognition
... the class label information during training Hand is detected using skin color and intrinsic geometry of the hand is used for gesture recognition The algorithm achieved 90% average recognition rate ... challenges in visual pattern recognition techniques assure wide scope for research Image feature extraction, feature selection, and classification are the different stages in a visual pattern recognition ... recognition, and Kalman filter based hand tracking in [79] The system uses skin color for static shape recognition and tracking The static shape recognition is performed using contour discriminant...
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Computational Intelligence In Manufacturing Handbook P3
... holonic concepts into a manufacturing setting: Holon: An autonomous and cooperative building block of a manufacturing system for transforming, transporting, storing, and/or validating information ... be applied to manufacturing enterprise integration, supply chain management, intelligent design, manufacturing scheduling and control, material handling, and holonic manufacturing systems 3.2 ... Heterarchical Scheduling for Flexible Manufacturing Systems, Proceedings of the 1995 International Joint Conference on Artificial Intelligence (IJCAI’95), Workshop on Intelligent Manufacturing, Montreal,...
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Computational Intelligence In Manufacturing Handbook P5
... Simulation of scheduling rules in a flexible manufacturing system using fuzzy logic, IEA-AIE96 Ninth International Conference on Industrial and Engineering Application of Artificial Intelligence and ... Part Dispatching Rules in FMSs This section explains a fuzzy real-time routing selection and an intelligent decision-making tool using fuzzy expert systems for machine loading in an FMS In the complex ... following criteria to be of most importance: ©2001 CRC Press LLC • • • • • • • Minimizing lateness/tardiness Minimizing makespan Maximizing system/machine utilization Minimizing WIP (work in process)...
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Computational Intelligence In Manufacturing Handbook P4
... components for cellular manufacturing, keeping a concurrent engineering framework in mind It utilizes two middle layers, as shown in Figure 4.4 The inputs for the network include design features ... themselves In the traditional part–machine incidence matrix, assuming binary values, sequence information is ignored To include sequence information, a sequence-based incidence matrix is introduced, ... cellular manufacturing (CM) systems ANNs also hold considerable promise, in general, for reducing complexity in logistics, and for streamlining and synergistic regrouping of many operations in the...
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Computational Intelligence In Manufacturing Handbook P7
... An intelligent design retrieving system should aim toward a natural linking of the next process planning and manufacturing stages 7.2.4 Conducting Retrieval Tasks with a Certain Degree of Incomplete ... engineering designs can be adapted in the research to represent a design One major disadvantage of using image-based indexing is that the disappearance of hidden features and internal lines is inevitable ... forming, Computers and Industrial Engineering, 26(1):93-104 Lim, S.S., et al., (1995) Multiple domain feature mapping: a methodology based on deep models of features, Journal of Intelligent Manufacturing, ...
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Computational Intelligence In Manufacturing Handbook P6
... design objectives may include minimizing intercellular movements, minimizing set-up time, minimizing machine load variation or maximizing machine utilization, and minimizing the system’s costs ... Algorithm for Finding the Optimum Process Routings for Parts The aim of a cellular manufacturing system design is minimizing the cost of the system It can be gained by dividing the system into independent ... The improvement in productivity is therefore essential for industries involved in batch manufacturing Group technology is a manufacturing philosophy for improving productivity in batch production...
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Computational Intelligence In Manufacturing Handbook P9
... crossover of two strings Input: Output: string-1 and string-2 offspring-1 and offspring-2 Determine a cut point randomly from all the positions of a string Each string is divided into two parts, ... to be used in order to convert a piece-part from its original form to a final form that is specified on a detailed engineering drawing For machining, process planning includes determination of ... used include conventional machines (e.g., horizontal and vertical milling, drilling, and grinding) and CNC machining centers 9.2.2 The Process Planning Problem Given a part and a set of manufacturing...
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Computational Intelligence In Manufacturing Handbook P8
... applying parallel machines in industrial manufacturing, only a handful of papers are found on sequencing machining operations for parallel machines [3, 22] The combinatorial nature of sequencing ... capability of activating i cutting tools (I Ն i Ն 1) on distinct MUs, in parallel, either for the purpose of machining a single workpiece, or for the purpose of machining, in parallel, l workpieces ... and 470 constraints This clearly indicates that sequencing the parallel machining operations by using conventional integer programming method could be computationally expensive and inefficient [4]...
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Computational Intelligence In Manufacturing Handbook P12
... of improving the product quality, increasing the effect events in production, increasing autonomity and intelligence in manufacturing lines, reducing the reaction time of manufacturing systems, ... and information processing tool for use in monitoring and control of manufacturing process In most manufacturing processes, the role of the artificial neural network is to perform signal processing, ... the network within the system Various manufacturing processes including machining, arc welding, semiconductor, and hydroforming processes are considered for networks applications Finally, perspectives...
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Computational Intelligence In Manufacturing Handbook P11
... or slip) Casting the slip in a plaster mold for a specified duration Removing the mold Air drying the cast piece Spray gazing the dried piece Firing the gazed piece in a kiln Inspecting the finished ... Machining Application Abrasive flow machining (AFM) was originally developed for deburring aircraft valve bodies It has many applications in the aerospace, automotive, electronic, and die-making industries ... Machining Using a Static Neural Network Model, Intelligent Engineering Systems through Artificial Neural Networks: Smart Engineering Systems: Neural Networks, Fuzzy Logic, Evolutionary Programming,...
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Computational Intelligence In Manufacturing Handbook P10
... Resource-Constrained Project Scheduling Problem Parallel Machine Scheduling Problem Job-Shop Scheduling Problem Multistage Process Planning Part Loading Scheduling Problem Introduction Production scheduling ... recent interest in using genetic algorithms to address the problem In the following sections, we explain how to solve them with genetic algorithms, including resource-constrained project scheduling, ... parallel machine scheduling, job-shop scheduling, multistage process planning, and part loading scheduling problem 10.2 Resource-Constrained Project Scheduling Problem The problem of scheduling activities...
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Tài liệu Computational Intelligence In Manufacturing Handbook P19 doc
... approximations, during which the training data set is split into certain training data set and possible training data set Subsequently, these training sets are forwarded to the GA-based search engine for ... training data set correctly For each certain rule extracted from the certain training data set, RClass* uses a so-called completeness index to indicate the number of observations in the original ... Induction, Int Journal of Advanced Manufacturing, in press Mrozek, A 1992 Rough Sets in Computer Implementation of Rule-Based Control of Industrial Process In Intelligent Decision Support — Handbook...
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Tài liệu Computational Intelligence In Manufacturing Handbook P18 pdf
... moving-window sample method is chosen, except that ARL values of the designs using the moving-window sample method are in general smaller than those using the independent method, considering ... method Applying the neural fuzzy method in SPC makes the pursuit of automation in quality engineering a possibility More research in this direction is needed as manufacturing and service industries ... the “true” individual observation input method in that it uses the most recent and four immediately passed observations The reason for maintaining a few observations in a sample point is due...
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