Search Results - (( based evaluation metric algorithm ) OR ( panel optimization strategical algorithm ))

Performance evaluation metrics for multi-objective evolutionary algorithms in search-based software engineering: systematic literature review by Nuh, Jamal Abdullahi, Koh, Tieng Wei, Baharom, Salmi, Osman, Mohd Hafeez, Kew, Si Na

“…Most of them either focused on solving newly re-formulated problems or on proposing new approaches, while a number of studies performed reviews and comparative studies on the performance of proposed algorithms. To evaluate such performance, it is necessary to consider a number of performance metrics that play important roles during the evaluation and comparison of investigated algorithms based on their best-simulated results. …”
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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.

Evaluation of Visual Network Algorithms on Historical Documents by Khairunnisa, Binti Ibrahim

“…Therefore, for a new document, evaluation of algorithms is ineluctable. The study also proposed a simple but reliable cluster evaluation metric called NPL-C metric. …”
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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

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Validation on an enhanced dendrite cell algorithm using statistical analysis by Mohamad Mohsin, Mohamad Farhan, Hamdan, Abdul Razak, Abu Bakar, Azuraliza, Abd Wahab, Mohd Helmy

“…This study demonstrates the mechanism of evaluating an enhanced algorithm using performance metrics and validated it using statistical analysis. …”
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LCSS-Based Algorithm for Computing Multivariate Data Set Similarity: A Case Study of Real-Time WSN Data by Khan, Rahim, Ali, Ihsan, Altowaijri, Saleh, Zakarya, Muhammad, Rahman, Atiq Ur, Ahmedy, Ismail, Khan, Anwar, Gani, Abdullah

“…Several non-metric-based algorithms are available in the literature, the most robust and reliable one is the dynamic programming-based technique. …”
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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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Multiobjective deep reinforcement learning for recommendation systems by Ee, Yeo Keat, Mohd Sharef, Nurfadhlina, Yaakob, Razali, Kasmiran, Khairul Azhar, Marlisah, Erzam, Mustapha, Norwati, Zolkepli, Maslina

“…The approaches were evaluated with movie recommendation dataset by using three conflicting metrics, namely precision, novelty, and diversity. …”
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Multi-objective deep reinforcement learning for recommendation systems by Keat, Ee Yeo, Mohd Sharef, Nurfadhlina, Yaakob, Razali, Kasmiran, Khairul Azhar, Marlisah, Erzam, Mustapha, Norwati, Zolkepli, Maslina

“…The approaches were evaluated with movie recommendation dataset by using three conflicting metrics, namely precision, novelty, and diversity. …”
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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

“…Three defects categories and one non-defect were chosen for this evaluation. The key metrics for the evaluation are classification accuracy, classification precision and classification recall. 855 images were used to train and test the algorithms. …”
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An intermediate significant bit (ISB) watermarking technique using neural networks by Zeki, A., Abubakar, A., Chiroma, H.

“…Many researchers have used these approaches to evaluate their algorithms. These strategies have been used for a long time, however, which unfortunately limits the value of PSNR and NCC in reflecting the strength and weakness of the watermarking algorithms. …”
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Heart Attack Prediction with Deep Learning by Syasya Putri binti Mohamad Razauddin

A Systematic Literature Review of Electricity Load Forecasting using Long Short-Term Memory by Salleh N.S.M., Suliman A., J�rgensen B.N.

Balancing Exploitation And Exploration Search Behavior On Nature-Inspired Clustering Algorithms by Alswaitti, Mohammed Y. T.

“…All the frameworks also achieved the first rank by the Friedman aligned-ranks (FA) test in all evaluation metrics. Moreover, the three frameworks provided convergent performances in terms of the repeatability. …”
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Cloudlet deployment and task offloading in mobile edge computing using variable-length whale and differential evolution optimization and analytical hierarchical process for decisio... by Daba, Layth Muwafaq Abdulhussein

“…Comparing this developed algorithm with other algorithms shows its superiority in multi-objective optimization (MOO) evaluation metrics. …”
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Data dissemination in VANETs using clustering and probabilistic forwarding based on adaptive jumping multi-objective firefly optimization by Hamdi, Mustafa Maad, Audah, Lukman, Rashid, Sami Abduljabbar

“…Comparing both AJ-MOFA and CFM with benchmarks using multi-objective optimization and networking metrics reveals the superiority in most evaluation measures, which makes them promising algorithms for data dissemination in VANETs. …”
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An intermediate significant bit (ISB) watermarking technique using neural networks by Zeki, Akram M., Abubakar, Adamu, Chiroma , Haruna

“…Many researchers have used these approaches to evaluate their algorithms. These strategies have been used for a long time, however, which unfortunately limits the value of PSNR and NCC in reflecting the strength and weakness of the watermarking algorithms. …”
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Data depublication using : Hashing algorithm / Naimah Nayan by Nayan, Naimah

“…The recommendation for future work is to evaluate various type of data and different type of hashing algorithm.…”
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Comparative evaluation of anomaly-based controller area network IDS by Sharmin, Shaila, Mansor, Hafizah, Abdul Kadir, Andi Fitriah, Abdul Aziz, Normaziah

“…However, these CAN IDS are often evaluated in disparate experimental settings, with different datasets and evaluation metrics, which hinder direct comparison. …”
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