Search Results - (( var optimization method algorithm ) OR ( data visualization learning algorithm ))
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Determining optimal location of static VAR compensator by means of genetic algorithm
Published 2011“…The purpose of this paper is to study a practical and accurate heuristic method known as genetic algorithm (GA) which is used to find the optimal location of Static Var Compensator (SVC) and its appropriate size and setting. …”
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Conference or Workshop Item -
2
Optimal design of three-phase static var compensation system
Published 2023“…This manuscript is aimed to emphasize the application of synchronous detection method (SDM) to develop and design three-phase static var compensation (SVC) systems with minimal complexity. …”
Conference paper -
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Sensitivity-based fuzzy multi-objective portfolio model with Value-at-Risk
Published 2019“…In addition, compared with the VaR-FMOPSM model, our sensitivity-based improved model with the IPSO algorithm also performs better than Genetic Algorithm and Simulate Anneal Algorithm (SA), it provides the same performance on this point. …”
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Genetic algorithm based method for optimal location placement of flexible ac transmission system devices for voltage profile improvement
Published 2011“…This thesis present a genetic algorithm based method for placement of FACTS devices for voltage profile improvement. …”
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Thesis -
5
Performance of correlational filtering and deep learning based single target tracking algorithms / ZhongMing Liao and Azlan Ismail
Published 2023“…Therefore, reviewing the visual target tracking algorithms based on deep learning from different perspectives is important. …”
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Optimization of support vector machine parameters in modeling of Iju deposit mineralization and alteration zones using particle swarm optimization algorithm and grid search method
Published 2023“…Copper deposits; Deposits; Geology; Learning algorithms; Mineralogy; Static Var compensators; Support vector machines; Three dimensional computer graphics; Alteration zones; Grid search; Grid-search method; Mineralization zone; Model Selection; Particle swarm optimization algorithm; Penalty parameters; Performance; Support vector classifiers; Support vectors machine; Particle swarm optimization (PSO); accuracy assessment; algorithm; classification; computer simulation; copper; geological survey; mineral alteration; mineralization; numerical model; ore deposit; parameterization; performance assessment; porphyry; resource assessment; support vector machine; three-dimensional modeling; Iran…”
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Interpretation of machine learning model using medical record visual analytics
Published 2021“…This paper analyzed several visual analytics ap- proach instantiated in machine learning algorithm for medical record analytics. …”
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Proceeding Paper -
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Algorithm visualization design guidelines for mobile leaning
Published 2018“…This study is about the algorithm visualization design guidelines for mobile platform, to teach students data structures and algorithm (DSA) subject effectively. …”
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Interpretation of machine learning model using medical record visual analytics
Published 2022“…This paper analyzed several visual analytics approaches instantiated in machine learning algorithm for medical record analytics. …”
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Proceeding Paper -
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Loss minimization with SVC installation using the Firefly Algorithm method / Syazana Abdul Halim
Published 2012“…This algorithm method is idealized by some of the characteristics of fireflies. …”
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Thesis -
12
Designing algorithm visualization on mobile platform: The proposed guidelines
Published 2017“…This paper entails an ongoing study about the design guidelines of algorithm visualization (AV) on mobile platform, helping students learning data structures and algorithm (DSA) subject effectively.Our previous review indicated that design guidelines of AV on mobile platform are still few.Mostly, previous guidelines of AV are developed for AV on desktop and website platform. …”
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13
On the Application of heuristic Method and Saddle Node Bifurcation for Optimal Placement of FACTS Devices in Power System
Published 2011“…This study focuses on an optimal placement of five major types of FACTS devices, namely, Static Var Compensator (SVC), Thyristor Controlled Series Compensator (TCSC), Static Synchronous Compensator (STATCOM), Static Synchronous Series Compensator (SSSC) and Unified Power Flow Controller (UPFC) in power system network using a well-known and applicable heuristic method known as genetic algorithm to seek the optimum location and setting of these controllers in the system. …”
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14
An Empirical Study on the Construction of A Non-Convex Risk Parity Portfolio using a Genetic Algorithm
Published 2025“…While conventional numerical methods can be applied, they often struggle with inefficiency and fail to deliver optimal results. …”
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15
Virtual reality in algorithm programming course: practicality and implications for college students
Published 2024“…The analysis of learning problems shows the unavailability of interactive learning media that can support various learning styles of students in programming algorithm materials. …”
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A hybrid spiking neural network model for multivariate data classification and visualization.
Published 2011“…This study proposes a hybrid model of Self-Organizing Map with modified adaptive coordinates (SOM-AC) and Spiking Neural Network (SNN) for multivariate spatial and temporal data visualization and classification. SOM is one of the most prominent unsupervised learning algorithms. …”
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Proceeding -
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A review on monocular tracking and mapping: from model-based to data-driven methods
Published 2022“…Astounding results from early methods based on filtering have intrigued the community to extend these algorithms using other forms of techniques like bundle adjustment and deep learning. …”
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Exploring employee working productivity: initial insights from machine learning predictive analytics and visualization / Mohd Norhisham Razali ... [et al.]
Published 2023“…Future research can explore more advanced machine learning algorithms, incorporate time-series analysis for temporal dependencies, and expand data collection from diverse organizational settings to improve the generalizability of predictive models.…”
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Sentiment Analysis of Sexual Harassment in Malaysia on Twitter Using Machine Learning Algorithms
Published 2023“…The transformed data is then modelled using machine learning algorithms such as Naïve Bayes classifier and Support Vector Machine to predict the overall sentiment of tweets, in which the finding depicted an overall positive sentiment surrounding the issue. …”
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Final Year Project Report / IMRAD
