Search Results - (( java detection machine algorithm ) OR ( program visualization optimization algorithm ))
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Features selection process can be considered a problem of global combinatorial optimization in machine learning. Genetic algorithm GA had been adopted to perform features selection method; however, this method could not deliver an acceptable detection rate, lower accuracy, and higher false alarm rates. …”
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Thesis -
2
Optimizing Visual Surveillance Sensor Coverage Using Dynamic Programming
Published 2017“…The main contribution of the paper is to introduce a dynamic programming algorithm, which defines an optimal policy for solving the visual sensor coverage problem. …”
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3
Simulation and Visualization of TSP Using Ant Colony Optimization
Published 2023“…The study concludes that optimization can be applied using programming language to provide users with comfortable and intelligible simulations and visualizations.…”
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4
Optimizing Visual Sensors Placement with Risk Maps Using Dynamic Programming
Published 2022“…This article explores the efficiency of the visual sensor placement based on a combination of two methods namely, a deterministic risk estimation for the risk assessment and a dynamic programming for optimizing the placement of surveillance cameras. …”
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5
Optimizing Visual Sensor Coverage Overlaps for Multiview Surveillance Systems
Published 2018“…This paper examines the coverage overlapping configurations in visual surveillance systems. This paper proposes a robust dynamic programming framework to optimize visual surveillance sensor coverage overlaps. …”
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6
Optimizing Visual Sensor Coverage Overlaps for Multiview Surveillance Systems
Published 2018“…This paper examines the coverage overlapping configurations in visual surveillance systems. This paper proposes a robust dynamic programming framework to optimize visual surveillance sensor coverage overlaps. …”
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Classification of students' performance in computer programming course according to learning style
Published 2024Conference Paper -
8
A Stepper Motor Design Optimization Using
Published 2005“…In this project, the program that has been developed is run to get the optimization result with Microsoft Visual C++. …”
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Monograph -
9
A Modified Giffler and Thompson Genetic Algorithm on the Job Shop Scheduling Problem
Published 2006“…This algorithm is modified to produce better results than the existing algorithm by using Visual Prolog programming language.…”
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Development of heuristic methods based on genetic algorithm (GA) for solving vehicle routing problem
Published 2008“…Based on the proposed heuristic method, we developed a program to optimize the routing problem using the Visual Studio C++ 6.0 programming language.…”
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Monograph -
11
Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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Classification of Students' Performance in Computer Programming Course According to Learning Style
Published 2024Proceedings Paper -
13
Mobile Vision-based Automatic Counting of Bacteria Colonies
Published 2017“…Fully automated and high throughput hardware imaging instruments are also available, but such machines are extremely costly. In this paper, we introduce a mobile based computer vision algorithm for automatic bacteria colony counting using morphological operations and transforms in image processing, on a custom Android mobile cross-platform open source software and written in Java, C++ and Open CV computer vision library. …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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16
Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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17
Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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18
Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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19
Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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20
An iterative procedure for production-inventory-distribution routing problem
Published 2015“…We propose a MatHeuristic algorithm, an optimization algorithm made by the interpolation of metaheuristics and mathematical programming techniques, to solve the model. …”
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