Search Results - (( evolution optimisation based algorithm ) OR ( program visualization system algorithm ))

Optimal placement, sizing and power factor of distributed generation: A comprehensive study spanning from the planning stage to the operation stage by Huy P.D., Ramachandaramurthy V.K., Yong J.Y., Tan K.M., Ekanayake J.B.

Performance evaluation and benchmarking of an extended computational model of ant colony system for DNA sequence design by Zuwairie, Ibrahim, Mohd Falfazli, Mat Jusof, Mohd Zaidi, Mohd Tumari

“…Ant colony system (ACS) algorithm is one of the biologically inspired algorithms that have been introduced to effectively solve a variety of combinatorial optimisation problems. …”
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A competitive co-evolutionary approach for the nurse scheduling problem by Mohamad Nazri, Maizatul Farhana, Mohd Yusoh, Zeratul Izzah, Basiron, Halizah, Daud, Azlina

“…The competitive approach further exhibits smoother convergence behaviour across generations, indicating stronger optimisation dynamics and improved robustness. These findings demonstrate that competitive co-evolution provides an effective and practical alternative to static fitness-based evolutionary methods for nurse scheduling, with broader applicability to healthcare scheduling and constraint optimisation problems.…”
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Ultrasonic Tomography System For Liquid/Gas Flow: Frame Rate Comparison Between Visual Basic And Visual C++ Programming by Abdul Rahim, Ruzairi, Mohd. Nayan, Norkharziana, Fazalul Rahiman, Mohd. Hafiz

“…In order to process and simulate a tomography system, it has been found that Visual C++ programming has an advantage one step ahead compared to Visual Basic programming. …”
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Optimizing Visual Surveillance Sensor Coverage Using Dynamic Programming by Altahir, A.A., Asirvadam, V.S., Hamid, N.H.B., Sebastian, P., Saad, N.B., Ibrahim, R.B., Dass, S.C.

“…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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A hyper-heuristic based strategy for image segmentation using multilevel thresholding by Luqman, Fakhrud Din, Shah Khalid, Kamal Zuhairi Zamli, Aftab Alam

“…EMCQ uses four low-level heuristic sets adopted from the teaching learning-based optimisation (TLBO) algorithm, flower pollination algorithm (FPA), genetic algorithm (GA), and Jaya algorithm. …”
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Simulation and Visualization of TSP Using Ant Colony Optimization by Tri Basuki, Kurniawan, Misinem, ., Astried, ., Joan Angelina, Widians

“…With Windows as the operating system and the C# programming language in Visual Studio 2019, the program complies with the Extreme Programming (XP) software development method. …”
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A hyper-heuristic based strategy for image segmentation using multilevel thresholding by Luqman, ., Fakhrud, Din, Shah, Khalid, Kamal Z., Zamli, Alam, Aftab

“…EMCQ uses four low-level heuristic sets adopted from the teaching learning-based optimisation (TLBO) algorithm, flower pollination algorithm (FPA), genetic algorithm (GA), and Jaya algorithm. …”
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Ray Casting for Iso-surface in Volumetric Data by Ngoc Anh, Do Hoang

“…It can be applied in many areas such as medical, oil and gas exploration, etc... Although volume visualization is highly computational cost, there is a vision of real time volumetric visualization systems based on interactive ray tracing. …”
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Stock market turning points rule-based prediction / Lersak Photong … [et al.] by Photong, Lersak, Sukprasert, Anupong, Boonlua, Sutana, Ampant, Pravi

“…Finally, rule-based optimisation techniques such as Particle Swarm Optimization (PSO), Differential Evolution (DE) and Grey Wolf Optimizer (GWO) were used to minimise the amount of time employed in the stock market turning points prediction. …”
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The A-rray: visual animation in learning structured programming / Wan Salfarina Wan Husain ,Siti Hasrinafasya Che Hassan and Wan Norliza Wan Bakar by Wan Husain, Wan Salfarina, Che Hassan, Siti Hasrinafasya, Wan Bakar, Wan Norliza

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Intelligent agent for e-commerce using genetic algorithm / Kok Sun Sun by Kok , Sun Sun

“…This system is achieved using the Genetic Algorithm which is capable of performing information retrieval and learning algorithm. …”
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The Development of Color Based Visual Search Utility by Mohamed, Al Mabruk S.

“…The system was implemented using Microsoft Visual C++ programming language and HTML. …”
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Optimizing Visual Sensor Coverage Overlaps for Multiview Surveillance Systems by Altahir, A.A., Asirvadam, V.S., Hamid, N.H.B., Sebastian, P., Saad, N.B., Ibrahim, R.B., Dass, S.C.

“…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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Optimizing Visual Sensor Coverage Overlaps for Multiview Surveillance Systems by Altahir, A.A., Asirvadam, V.S., Hamid, N.H.B., Sebastian, P., Saad, N.B., Ibrahim, R.B., Dass, S.C.

“…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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Web-based RIG performance reporting system using interactive visualization techniques / Amir Hambaly Nasaruddin by Nasaruddin, Amir Hambaly

“…D3.js is used as a technology to visualize the result in interactive form or dynamic visualization which is a JavaScript library and Python is a language to program the system. …”
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Thalassaemia detection using CBR Algorithm via mobile device by Nur Faezah, Omar

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Sentiment Analysis of Airline Reviews Using Naive Bayes Algorithm / Ahmad Firdaus Maliki by Maliki, Ahmad Firdaus

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A network based fetal ECG monitoring algorithm by Ibrahimy, Muhammad Ibn, Hasan , M. A., Motakabber, S. M. A.

“…The hardware part is developed for abdominal Electrocardiography (AECG) data acquisition system. Individual algorithms and customized application software are developed using Visual Basic for both the networking and Fetal Heart Rate (FHR) monitoring systems. …”
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B-spline curve fitting with different parameterization methods by Kheng, Jia Shen

“…After generating control points, distance between the generated and original data points is used to identify the error of the algorithm. Later, genetic algorithm and differential evolution optimization are used to optimise the error of the curve. …”
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