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A Framework of Rough Reducts Optimization Based on PSO/ACO Hybridized Algorithms by Pratiwi, Lustiana, Choo, Yun Huoy, Draman @ Muda, Azah Kamilah

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Classification of basal stem rot disease in oil palm using dielectric spectroscopy by Al-Khaled, Al-Fadhl Yahya Khaled

“…An analysis was done to see the effect of implementing different data reduction algorithms in classifying BSR disease. …”
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Development of a phantom and metal artifact correction (MAC) algorithm for post-operative spine computed tomography (CT) imaging / Noor Diyana Osman by Osman, Noor Diyana

“…The last part is the development of a metal artifact correction (MAC) algorithm and evaluation of the proposed algorithm in artifacts reduction in CT images. …”
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Predicting Accuracy of Income a Year Using Rough Set Theory by Zuraihah, Ngadengon

“…The result obtained from the experiments showed that the best discretization method is Naive Algorithm, the best split factor is 0.6, the best reduction method is Johnson's Algorithm and the best classifier is Standard Voting. …”
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Enhancing obfuscation technique for protecting source code against software reverse engineering by Mahfoudh, Asma

“…The proposed technique can be enhanced in the future to protect games applications and mobile applications that are developed by java; it can improve the software development industry. …”
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Efficient hybrid reduction for binary based information system in soft set theory by Mohd Rose, Ahmad Nazari

“…With SRR (Soft Set Rough Reduction) and Parameter Reduction (PR) being ineffective with respect to consistency and accuracy, further analysis on the data size achieved by HRSS and Normal Parameter Reduction (NPR) were then considered. …”
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Architecture for latency reduction in healthcare internet-of-things using reinforcement learning and fuzzy based fog computing by Shukla, S., Hassan, M.F., Jung, L.T., Awang, A.

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Architecture for latency reduction in healthcare internet-of-things using reinforcement learning and fuzzy based fog computing by Shukla, S., Hassan, M.F., Jung, L.T., Awang, A.

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Mathematical models and optimization algorithms for low-carbon Location-Inventory-Routing Problem with uncertainty by Liu, Lihua

“…This thesis also aims to solve the low-carbon LIRP model with uncertainty factors such as carbon trading, customer demand, shortages, and soft time windows using advanced algorithms. …”
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A low complexity resource allocation algorithm for OFDMA cooperative relay networks with fairness and QoS guaranteed by Salah, Asem A., Raja Abdullah, Raja Syamsul Azmir, Mohd Ali, Borhanuddin, Odeh, Nidhal A.

“…The results show that the proposed algorithm outperforms the greedy and static algorithms in terms of outage probability and fairness, and at the same time outperforms Jeong's algorithm by 58% in terms of total sum rate, with an average 74% reduction in system complexity.…”
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Feature Selection Based on Grey Wolf Optimizer for Oil Gas Reservoir Classification by Al-Tashi, Q., Rais, H.M., Abdulkadir, S.J., Mirjalili, S.

“…However, the high dimensionality or irrelevant measurements/features of the reservoir data leads to less classification accuracy of the factor reservoir recovery. …”
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Study on sparseness effects over NMF applied for automatic text summarization by Batcha, Nowshath Kadhar, Murugesan, Raja Kumar, A. Aziz, Normaziah

“…Interpretation defines the ease at which the structure of high dimensional data can be understood. While, storage capability relates to the extent of data reduction process achieved by NMF. …”
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Enhanced PAPR reduction and channel estimation techniques in multi-carrier wireless communication system by Ali Kareem, Nahar

“…First, a novel rotating phase shift (RPS) based on signal scrambling to reduce PAPR in OFDM system had been proposed. The search algorithm was used to solve the convex problem in selecting PAPR-RPS best phase shift factor based on the cost of computational complexity. …”
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PSO and Linear LS for parameter estimation of NARMAX/NARMA/NARX models for non-linear data / Siti Muniroh Abdullah by Abdullah, Siti Muniroh

“…Additionally, the PSO algorithm was found to improve the correlation tests (reduction in correlation violation 22.22% in DCM NARX, 1.89% in FRA NARMAX and 10.46% in MG NARMA experiment) relative to the LLS algorithms.…”
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Analysis of Traffic Accident Patterns Using Association Rule Mining by Yudy, Pranata, Tri Basuki, Kurniawan, Edi Surya, Negara, Ahmad Haidar, Mirza

“…This study analyzed the levels of minor, moderate, and severe traffic accidents in the Palembang Police area from 2015 to 2020 using association rule mining and the apriori algorithm. The study established valuable insights into accident trends and contributing factors by leveraging traffic accident data and determining variable relationships. …”
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Learning analytic framework for students’ academic performance and critical learning pathways by Lyn, Jessica Tan Yen, Goh, Yong Kheng, Lai, An Chow, Ngeow, Yoke Meng

“…This framework’s methodology involves several key steps, starting with standardized data collection and pre-processing. Subsequently, dimensionality reduction techniques like Principal Component Analysis (PCA) and Non-negative matrix factorization (NMF) are applied to capture the most influential course components and grade information. …”
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Modeling And Optimization Of Physical Vapour Deposition Coating Process Parameters For Tin Grain Size Using Combined Genetic Algorithms With Response Surface Methodology by Mohamad Jaya, Abdul Syukor, Muhamad, Mohd Razali, Abd Rahman, Md Nizam, Mohammad Jarrah, Mu'ath Ibrahim, Hasan Basari, Abd Samad

“…Additionally,analysis of variance(ANOVA) was used to determine the significant factors influencing resultant TiN coating grain size.Based on that,a quadratic polynomial model equation was developed to represent the process variables and coating grain size.Then,in order to optimize the coating process parameters, genetic algorithms (GAs) were combined with the RSM quadratic model and used for optimization work.Finally,the models were validated using actual testing data to measure model performances in terms of residual error and prediction interval (PI).The result indicated that for RSM,the actual coating grain size of validation runs data fell within the 95% (PI) and the residual errors were less than 10 nm with very low values, the prediction accuracy of the model is 96.09%.In terms of optimization and reduction the experimental data,GAs could get the best lowest value for grain size then RSM with reduction ratio of ≈6%, ≈5%, respectively.…”
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Predicting Student Performance in Object Oriented Programming Using Decision Tree : A Case at Kolej Poly-Tech Mara, Kuantan by Mohd Hanis, Rani, Abdullah, Embong

“…The dataset was run through some pre-processing such as data cleaning, data reduction and discretization. …”
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Combination of perturb and observe with online sequential extreme learning machine for photovoltaic system maximum power point tracking by Dira, Yasir Sabah

“…From different MPPT techniques previously proposed, the online sequential extreme learning machine algorithm and conventional perturb and observe are combined together as a proposed MPPT algorithm. …”
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Optimization Of 3d Reconstruction Surface Rendering Algorithm For Osferion Bone Void Filling by Chin, Daniel Jie Yuan

“…The proposed improvement method, which is Marching Cubes with 3D data smoothing and surface smoothing box kernel size of 11, mesh decimation reduction factor of 0.1, successfully increased the reconstruction accuracy by 6.26%, decreased the number of vertices and faces by 89.82%, and decreased the reconstruction and rendering time by 52.45% and 90.74% seconds respectively…”
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