Search Results - (( model evaluation metric algorithm ) OR ( swarm optimization max algorithm ))*

A particle swarm optimization and min-max­-based workflow scheduling algorithm with QoS satisfaction for service-­oriented grids by Ambursa, Faruku Umar, Latip, Rohaya, Abdullah, Azizol, K. Subramaniam, Shamala

“…It also outperforms the comparison algorithm, with about 30% increase, in terms of cumulative QoS satisfaction of optimization requirements. …”
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Performance comparison of differential evolution and particle swarm optimization in constrained optimization by Iwan, Mahmud, Akmeliawati, Rini, Faisal, Tarig, Al-Assadi, Hayder M.A.A.

“…Particle swarm optimization (PSO) and differential evolution (DE) are among the well-known modern optimization algorithms. …”
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Data normalization techniques in swarm-based forecasting models for energy commodity spot price by Yusof, Yuhanis, Mustaffa, Zuriani, Kamaruddin, Siti Sakira

“…Data mining is a fundamental technique in identifying patterns from large data sets.The extracted facts and patterns contribute in various domains such as marketing, forecasting, and medical.Prior to that, data are consolidated so that the resulting mining process may be more efficient.This study investigates the effect of different data normalization techniques.which are Min-max, Z-score and decimal scaling, on Swarm-based forecasting models.Recent swarm intelligence algorithms employed includes the Grey Wolf Optimizer (GWO) and Artificial Bee Colony (ABC).Forecasting models are later developed to predict the daily spot price of crude oil and gasoline.Results showed that GWO works better with Z-score normalization technique while ABC produces better accuracy with the Min-Max.Nevertheless, the GWO is more superior than ABC as its model generates the highest accuracy for both crude oil and gasoline price.Such a result indicates that GWO is a promising competitor in the family of swarm intelligence algorithms.…”
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Artificial neural network-salp-swarm algorithm for stock price prediction by Zuriani, Mustaffa, Mohd Herwan, Sulaiman, Azlan, Abdul Aziz

“…Additionally, the SSA-ANN model is compared with other two hybrid models: the ANN optimized by the Whale Optimization Algorithm (WOA-ANN) and Moth-Flame Optimizer (MOA-ANN), as well as a single model, namely the Autoregressive Integrated Moving Average (ARIMA). …”
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A quantum-inspired particle swarm optimization approach for environmental/economic power dispatch problem using cubic criterion function by Mahdi, F.P., Vasant, P., Abdullah-Al-Wadud, M., Watada, J., Kallimani, V.

“…Many-objective EED problems are defined by using a cubic criterion function, and a max/max price penalty factor is considered to convert all the objectives into a single objective to compare the final results with other well-known methods found in the literature like Lagrangian relaxation, particle swarm optimization, simulated annealing, and quantum-behaved bat algorithm. …”
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A quantum-inspired particle swarm optimization approach for environmental/economic power dispatch problem using cubic criterion function by Mahdi, F.P., Vasant, P., Abdullah-Al-Wadud, M., Watada, J., Kallimani, V.

“…Many-objective EED problems are defined by using a cubic criterion function, and a max/max price penalty factor is considered to convert all the objectives into a single objective to compare the final results with other well-known methods found in the literature like Lagrangian relaxation, particle swarm optimization, simulated annealing, and quantum-behaved bat algorithm. …”
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Interacted Multiple Ant Colonies for Search Stagnation Problem by Aljanabi, Alaa Ismael

“…Ant Colony Optimization (ACO) is a successful application of swarm intelligence. …”
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Reactive memory model for ant colony optimization and its application to TSP by Sagban, Rafid, Ku-Mahamud, Ku Ruhana, Abu Bakar, Muhamad Shahbani

“…Ant colony optimization is one of the most successful examples of swarm intelligent systems. …”
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Electric vehicle battery state of charge estimation using metaheuristic-optimized CatBoost algorithms by Mohd Herwan, Sulaiman, Zuriani, Mustaffa, Ahmad Salihin, Samsudin, Amir Izzani, Mohamed, Mohd Mawardi, Saari

“…A comprehensive data preprocessing pipeline was implemented, including missing value treatment, outlier removal, and feature normalization using Min-Max scaling. Three distinct metaheuristic algorithms were investigated: Barnacles Mating Optimizer (BMO), Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Whale Optimization Algorithm (WOA), each integrated with CatBoost to optimize critical parameters including learning rate, tree depth, regularization, and bagging temperature. …”
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Performance comparison of GA and PSO based ANN training on medical dataset / Muhammad Amirul Danish Jamal by Jamal, Muhammad Amirul Danish

“…This research performs a comparative analysis of Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) as methods for optimizing the training of ANNs, utilizing three medical datasets: Breast Cancer Wisconsin, Cleveland Heart Disease, and Pima Indian Diabetes. …”
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Software metrics selection model for predicting maintainability of object-oriented software using genetic algorithms by Bakar, Abubakar Diwani

“…The latest effort to solve this selection problem is the development of the metrics selection model that uses genetic algorithm (GA). …”
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Social spider optimisation algorithm for dimension reduction of electroencephalogram signals in human emotion recognition by Al-Qammaz, Abdullah Yousef, Ahmad, Farzana Kabir, Yusof, Yuhanis

“…Due to some limitations of current heuristics and evolutionary algorithms, this paper proposed a new swarm based algorithm for feature selection method called Social Spider Optimization (SSO-FS). …”
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Improving Accuracy Metric with Precision and Recall Metrics for Optimizing Stochastic Classifier by Hossin, M., Sulaiman, M.N, Mustapha, N., Rahmat, R.W

“…In this study, we propose a new evaluation metric that combines accuracy metric with the extended precision and recall metrics to negate these detrimental effects. …”
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Improving accuracy metric with precision and recall metrics for optimizing stochastic classifier by Hossin, Mohammad, Sulaiman, Md. Nasir, Mustapha, Norwati, O. K. Rahmat, Rahmita Wirza

“…In this study, we propose a new evaluation metric that combines accuracy metric with the extended precision and recall metrics to negate these detrimental effects. …”
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Improving accuracy metric with precision and recall metrics for optimizing stochastic classifier by M., Hossin, M.N., Sulaiman, N., Mustpaha, R.W., Rahmat

“…In this study, we propose a new evaluation metric that combines accuracy metric with the extended precision and recall metrics to negate these detrimental effects.We refer the new evaluation metric as optimized accuracy with recall-precision (OARP). …”
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A Systematic Literature Review of Machine Learning Methods for Short-term Electricity Forecasting by Md Salleh N.S., Suliman A., Jorgensen B.N.

Role Minimization As An Optimization Metric In Role Mining Algorithms : A Literature Review by Ahmad, Rabiah, Abd Hamid, Nazirah, Selamat, Siti Rahayu

“…A recent access control model that could accommodate a dynamic structure such as cloud computing can be recognized as role based access control and the role management process of this access control can be identified as role mining.The current trend in role based access control is the role mining problem that can be described as the difficulty to uncover an optimum set of roles from the userpermission assignment.To solve this problem,the researchers have proposed role mining algorithms to produce role set and among the existing algorithms there is an intrinsic topic of the common perception to evaluate the goodness of the generated role set.Eventually,the value of the identified roles could be measured by the preferred metric of optimality namely the number of roles,sizes of userassignment and permission-assignment and Weighted Structural Complexity.Until now, there is some disagreement on the optimization metric but notably many researchers have agreed on the minimization of the number of roles as a solid metric.This paper discusses an overview of the current state-of-the-art on the recent role mining algorithms that focus on role minimization as an optimization metric to evaluate the goodness of the identified roles. …”
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Efficient region of interest based metric learning for effective open world deep face by Faizabadi, Ahmed Rimaz, Mohd Zaki, Hasan Firdaus, Zainal Abidin, Zulkifli, Nik Hashim, Nik Nur Wahidah, Husman, Muhammad Afif

“…To establish the effectiveness, we investigated various threshold finding strategies for five state-of-the-art face recognition algorithms for open world adaptation on different datasets.We also proposed a novel performance evaluation metric for FR algorithms on imbalanced datasets. …”
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Evaluation of the Transfer Learning Models in Wafer Defects Classification by Jessnor Arif, Mat Jizat, Anwar, P. P. Abdul Majeed, Ahmad Fakhri, Ab. Nasir, Zahari, Taha, Yuen, Edmund, Lim, Shi Xuen

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Scheduling tight deadlines for scientific workflows in the cloud by Bajaher, Awadh Salem Saleh

“…The results show that the PDC performs better in term of success rate metric while the DCCP algorithm has better performance in term of normalized cost metric. …”
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