Search Results - (( parallel classification modeling algorithm ) OR ( problem implementation using algorithm ))

Robust tweets classification using arithmetic optimization with deep learning for sustainable urban living by Hamza, Manar Ahmed, Hassan Abdalla Hashim, Aisha, Motwakel, Abdelwahed, Elhameed, Elmouez Samir Abd, Osman, Mohammed, Kumar, Arun, Singla, Chinu, Munjal, Muskaan

“…At last, tuning of parameters related to parallel BiGRU model performed by AOA. An wide set of tests carried out to illustrate better performance of AOADL-TC model. …”
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Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining. by Saeed, Walid

“…Therefore generating a good decision model or classification model is a major component in many data mining researches. …”
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EMG motion pattern classification through design and optimization of neural network by Ahsan, Md. Rezwanul, Ibrahimy, Muhammad Ibn, Khalifa, Othman Omran

“…The ANN models work in parallel thus providing higher computational performance than traditional classifiers which function sequentially. …”
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EMG motion pattern classification through design and optimization of Neural Network by Md. Rezwanul, Ahsan, Muhammad Ibn, Ibrahimy, Othman Omran, Khalifa

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Model of Improved a Kernel Fast Learning Network Based on Intrusion Detection System by Ali, Mohammed Hasan, Mohamed Fadli, Zolkipli

“…The approach was tested on the KDD Cup99 intrusion detection dataset and the results proved the proposed PSO-RKFLN as an accurate, reliable, and effective classification algorithm.…”
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Random sampling method of large-scale graph data classification by Rashed Mustafa, Mohammad Sultan Mahmud, Mahir Shadid

“…Finally, we classified the graphs of data blocks using the SVM algorithm. In experimental evaluation, our proposed method outperformed state-of-the-art graph kernels on graph classification datasets in terms of accuracy.…”
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VLSI Design of a neurohardware processor implementing the Kohonen Neural Network algorithm by Rajah, Avinash

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Quantum Processing Framework And Hybrid Algorithms For Routing Problems by Soltan Aghaei, Mohammad Reza

“…The focus of this study is developing a framework of QAPU and hybrid architecture for classical-quantum algorithms. The framework is used to increase the implementation performance of quantum algorithms. …”
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Low-level hybridization scripting language with dynamic parameterization in PSO-GA / Suraya Masrom by Masrom, Suraya

“…However, in many cases, implementing the suitable hybrid algorithms for a given optimization problem is a considerably difficult, which in most cases, is time consuming. …”
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Festive season balancing groceries optimization / Fairuz Mohamed Razi by Mohamed Razi, Fairuz

“…This research uses Genetic Algorithms concept and technique to solve an optimization problem in shortage in supply-demand during festive season which is during Hari Raya Aidilfitri. …”
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The Implementation of Genetic Algorithm in Path Optimization by Jumali, Suriana

“…In this project, TSP will be used to model and easy visualize the path optimization problem and Genetic Algorithm (GA) was chosen to be implemented in resolving the problem. …”
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Enhancing Market-Based Scheduling Algorithm on Globally Distributed Web Servers Using Least Suitable Sealed Bid Technique by Al-Ewiwi, Mahmoud

“…Scheduling of a multiple distributed servers is considered as a complex problem.considered as NP-complete problem,where no single efficient algorithm guaranteed to produce optimal results.This thesis investigates on how to find optimal solution for distribute system,by implementing market based scheduling Algorithm(MBSA).On implementing the MBSA, a new auction technique which is the least suitable sealed bid auction will be introduced.it is found that least suitable sealed bid technique will give the close-to-optimum solution.In the implementation, cooperative agents were used as a middleware between web servers and stand-alone schedulers. …”
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Hybrid harmony search-artificial intelligence models in credit scoring by Goh, Rui Ying

“…With the parallelization of MHS hybrid models, the computational time is effectively reduced, with RF hybrid models faster than SVM hybrid models. …”
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Diagnosis of eyesight using Improved Clonal Selection Algorithm (ICLONALG) / Nor Khirda Masri by Masri, Nor Khirda

“…This study aims to implement the classification algorithm using the Improved Clonal Selection Algorithm (ICLONALG) to classify the eyesight’s problems. …”
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Metric's thresholds for encoding evolutionary computing representation in software engineering problem by Md Sultan, Abu Bakar, Din, Jamilah, Zulzalil, Hazura, Bakar, Abubakar Diwani

“…The software metrics selection problem is among the problems implemented using this technique. …”
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An experimental study of neighbourhood based metaheuristic algorithms for test case generation satisfying the modified condition / decision coverage criterion by Haque, Ariful

“…We have chosen four neighborhood based algorithms which are commonly used in optimization problems and divided them in newly implemented and re-implemented category. …”
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A hybrid algorithm for finding shortest path in network routing. by Soltan Aghaei, Mohammad Reza, Ahmad Zulkarnain, Zuriati, Mamat, Ali, Zainuddin, Hishamuddin

“…This wave gives an O( N ) steps quantum algorithm for identifying that record, where was used classical Dijkstra’s algorithm for finding shortest path problem in the graph of network and implement quantum search. …”
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Simulation of shortest path using a-star algorithm / Nurul Hani Nortaja by Nurul Hani , Nortaja

“…The steps to calculate a shortest path using A • algorithm is shown by using appropriate examples and related figures. …”
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Optimal path planning algorithm for swarm robots using bat algorithm with mutation (bam) by Lim, Pei Yee

“…However, there is still room for improvement such as implementing the obstacle avoidance algorithm into swarm robot. …”
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Faculty timetabling using genetic algorithm by Liong, Boon Yaun

“…Faculty Timetabling using Genetic Algorithm (FTGA) is an application that generate optimum timetable for faculty.The target user of this application is faculty staff who responsible in generate timetable.The problem statement of the project is many clashing exist in the timetable.Faculty staff needs to solve the clashing manually.This will waste time and it is a problem for staff to solve the clashing.By implement GA,clashing will be reduced.The objective of the project is to develop aprototype in scheduling application for generates an optimum timetable for a faculty.Genetic algorithm will be implemented.The scope of FTGA is Faculty of Computer Systems & Software Engineering (FCSSE).The methodology use in this project is prototype model.The testing result show 95 out of 100 test cases achieved the maximum fitness value which means there is no clashing in the timetable.The maximum generation is set to 15 generation.Population for each generation is 3 populations.Percentage of FTGA solve the problem is 95%.…”
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