Search Results - (( java implementation path algorithm ) OR ( pattern execution _ algorithm ))
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Heavy Transportation Shortest Route using Dijkstra’s algorithm (HETRO) / Nurul Aqilah Ahmad Nezer
Published 2017“…The development tools used in developing this project is NetBeans by using Java for the implementation of the coding. The methodology that used for developing this system is the Dijkstra’s algorithm. …”
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Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization
Published 2019“…BST inserts the nodes in the way that the Dijkstra’s can find the empty parking in fastest way. Dijkstra’s algorithm initials the paths to finding the shortest path while ACO optimizes the paths. …”
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Path planning for unmanned aerial vehicle (UAV) using rotated accelerated method in static outdoor environment
Published 2021“…In this study, a fast iterative method known as Rotated Successive Over-Relaxation (RSOR) is introduced. The algorithm is implemented in a self-developed 2D Java tool, UAV Planner. …”
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Smart appointment organizer for mobile application / Mohd Syafiq Adam
Published 2009“…The main component of this prototype is the use of Dijkstra algorithm to compute the shortest path from source of appointment to the 6 points of destinations within UiTM Shah Alam. …”
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Parallel implementation on improved error signal of backpropagation algorithm
Published 2001“…Experimental results shows that the execution time of the parallel version is much less than the execution time of the sequential version. …”
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Performance of IF-Postdiffset and R-Eclat Variants in Large Dataset
Published 2018“…This paper proposes IF-Postdiffset as a new variant in R-Eclat algorithm. This paper also highlights the performance of infrequent mining pattern from the transaction database among different variants of the R-Eclat algorithm regarding its execution time.…”
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A frequent pattern mining algorithm based on FP-growth without generating tree
Published 2010“…Our algorithm works based on prime factorization, and is called Frequent Pattern-Prime Factorization (FPPF).…”
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A frequent pattern mining algorithm based on FP-growth without generating tree
Published 2010“…It then divides the compressed database into a set of conditional databases (a special kind of projected database), each associated with one frequent item or pattern fragment, and mines each such database separately.For a large database, constructing a large tree in the memory is a time consuming task and increase the time of execution.In this paper we introduce an algorithm to generate frequent patterns without generating a tree and therefore improve the time complexity and memory complexity as well.Our algorithm works based on prime factorization, and is called Frequent Pattern- Prime Factorization (FPPF).…”
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Linear-pso with binary search algorithm for DNA motif discovery / Hazaruddin Harun
Published 2015“…The Linear-PSO algorithm was the first version of improvement. However due to the longer time required for complete execution of this algorithm, the Binary Search technique was integrated and a new version of the algorithm was developed, namely the Linear-PSO with Binary Search (LPBS) algorithm. …”
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11
Using unique-prime-factorization theorem to mine frequent patterns without generating tree
Published 2011“…However, for a large database, constructing a large tree in the memory is a time consuming task and increase the time of execution. In this study we introduce an algorithm to generate frequent patterns without generating a tree and therefore improve the time complexity and memory complexity as well. …”
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Ant colony algorithm for text classification in multicore-multithread environment / Ahmad Nazmi Fadzal
Published 2017“…ACO classification accuracy is compared to Genetic Algorithm classifier which also a wrapper method. On integration of the technique, ACO is proposed to work in a multicore-multithread environment to gain additional execution time advantage. …”
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13
Artificial immune system based on real valued negative selection algorithms for anomaly detection
Published 2015“…With respect to all the algorithms, V-Detector proved to be superior and surpassed all other algorithms based on performance and execution time.…”
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14
Integration of zero and sequential algorithm in shuffle exchange with Minus One Stage
Published 2013“…This paper also shows the details of the illustrative examples used to explain each algorithm. At the end of this chapter, the comparative analysis shows the performance of each algorithm with the integration of shuffle exchange connection pattern in terms of the execution time and number of passes.…”
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Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection
Published 2008“…A comprehensive performance study has been reported that PrefixSpan, one of the sequential pattern mining algorithms, outperforms GSP, SPADE, as well as FreeSpan in most cases, and PrefixSpan integrated with pseudoprojection technique is the fastest among those tested algorithms. …”
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Grid-Based Classifier as a Replacement for Multiclass Classifier in a Supervised Non-Parametric Approach
Published 2009“…The quality of a given classification technique is measured by the computational complexity, execution time of algorithms, and the number of patterns that can be classified correctly despite any distribution. …”
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The analysis of road traffic fatality pattern for Selangor, Malaysia case study
Published 2021“…The preliminary data screening shows that road traffic crash patterns and road traffic fatality patterns in Selangor have many similarities. …”
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Neural Network Based Pattern Recognition in Visual Inspection System for Intergrated Circuit Mark Inspection
Published 1998“…Error-back propagation algorithm was used to train the network. The objective was to test the robustness of the network in handling pattern variations as well as the feasibility of implementing it on the production floor in tetms of execution speed. …”
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Machine learning predictions of stock market pattern using Econophysics approach
Published 2025“…Hence, this research will be using Monte Carlo Simulation and identify which machine learning algorithm is suitable for predicting stock market patterns. …”
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