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Parallel distributed genetic algorithm development based on microcontrollers framework by Krishnan P.S., Kiong T.S., Koh J.

Sizing optimization of large-scale grid connected photovoltaic system using dolphin echolocation algorithm / Muhammad Zakyizzuddin Rosselan by Rosselan, Muhammad Zakyizzuddin

“…Before incorporating the optimization methods, a sizing algorithm for large-scale GCPV systems was developed. …”
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Common spatial pattern with feature scaling (FSc-CSP) for motor imagery classification by Prathama, Y.B.H., Shapiai, M.I., Aris, S.A.M., Ibrahim, Z., Jaafar, J., Fauzi, H.

“…In this paper, we propose an algorithm called Feature Scaling Common Spatial Pattern (FSc-CSP) to overcome the problem of feature selection. …”
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An Efficient Genetic Algorithm for Large Scale Vehicle Routing Problem Subject to Precedence Constraints by Noraini, Mohd Razali

“…Therefore, it can be stated that the genetic algorithm approach developed in this study is efficient in solving large scale vehicle routing problem subject to precedence constraints with the objective of minimizing the distance travelled.…”
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Performance-aware cost-effective brokering and load balancing algorithms for data center in large scale cloud computing by Naha, Ranesh Kumar

“…In order to make our proposed method cost efficient, we developed Load Aware Over Cost algorithm which is 8% cost effective comparing with Load Aware algorithm. …”
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Robust variable selection methods for large- scale data in the presence of multicollinearity, autocorrelated errors and outliers by Uraibi, Hassan S.

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Facial features point localization using modified SIFT scale space / Zulfikri Paidi by Paidi, Zulfikri

“…The issue mentioned requires a new action to resolve it. This study aimed to develop a new algorithm in the form of hybrids when the scaling technique in SIFT was integrated with another technique. …”
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Not seeing the forest for the trees: Generalised linear model out-performs random forest in species distribution modelling for Southeast Asian felids by Chiaverini, Luca, Macdonald, David W., Hearn, Andrew J., Kaszta, Zaneta, Ash, Eric, Bothwell, Helen M., Can, Ozgun Emre, Channa, Phan, Clements, Gopalasamy Reuben *, Haidir, Iding Achmad, Kyaw, Pyae Phyoe, Moore, Jonathan H., Rasphone, Akchousanh, Tan, Cedric Kai Wei, Cushman, Samuel A.

“…Our results have strong implications for SDM development, revealing the inconsistencies introduced by the choice of algorithm on scale optimisation, with GLM selecting broader scales than RF.…”
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A Study On Gene Selection And Classification Algorithms For Classification Of Microarray Gene Expression Data by Yeo, Lee Chin, Deris, Safaai

“…The Development Of Microarray Technology Allows Researchers To Monitor The Expression Of Genes On A Genomic Scale. …”
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Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares by Uraibi, Hassan Sami

“…We modified the classical bootstrapping algorithm by developing a mechanism based on the robust LTS method to detect the correct number of outliers in the each bootstrap sample. …”
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Toxic Gas Dispersion Model Based On Neural Pattern Recognition Networks by Roslan, Nurfarah Arina

“…To achieve the objectives, two phases of structure architecture of NPR is carried out. First, NPR development is developed using three different algorithms which are Levenberg-Marquart (LM), Bayesian Regularization (BR) and Scaled Conjugated Gradient (SCG) to propose the best network algorithm using 70% training and 10-28 hidden neurons. …”
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Optimization of RFID network planning for monitoring railway mechanical defects based on gradient-based Cuckoo search algorithm by Talib, Nihad Hasan

“…In the large-scale area application, the GBCS algorithm achieved 100%, 93.75%, and 98.9% coverage for Maluri, Subang, and TBS stations, respectively. …”
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Efficient genetic partitioning-around-medoid algorithm for clustering by Garib, Sarmad Makki Mohammed

“…The first set showed the efficiency and performance of the proposed composing techniques including: kmean++ algorithm for initialization, fitness scaling for fitness selection, the proposed split and merge mutation operator, and choosing the medoid instead of the mean as a centroid-selection schema. …”
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Development of artificial neural network models for predicting lipid profile using smartMF electrical parameters / Ahmad Zulkhairi Zulkefli by Ahmad Zulkhairi , Zulkefli

“…For TG, the LM algorithm with a testing accuracy of 76.7%, sensitivity of 28.6% and specificity of 91.3% was selected. …”
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Nomadic people optimizer (NPO) for large-scale optimization problems by Mohamd Salih, Sinan Qahtan

“…The final problem is the ability of the algorithm to solve large-scale problems, which mostly are the real world problems. …”
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Steganography based on utilizing more surrounding pixels by Afrakhteh, Masoud

“…The purpose of this study is to investigate the application of least significant bit insertion method (LSB) in concealing a definite amount of message bits inside a typical media such as an 8-bit gray-scale image and develop an alternative model structure selection algorithm based on considering more surrounding pixels in order to compute the best capacity value for each target pixel. …”
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A comparative study and simulation of object tracking algorithms by Ji, Yuanfa, Yin, Pan, Sun, Xiyan, Kamarul Hawari, Ghazali, Guo, Ning

“…The simulation experiment obtained the accuracy figure and success figure of the overall performance comparison of these 50 object tracking algorithms and then selected 11 attributes to compare the performance of various algorithms. …”
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Performance of various training algorithms on scene illumination classification by Hesamian, Mohammad Hesam, Mashohor, Syamsiah, Saripan, M. Iqbal, Wan Adnan, Wan Azizun, Hesamian, B., Hooshyari, M. M.

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Pattern classifier of chemical compounds in different qualities of agarwood oil parameter using scale conjugate gradient algorithm in MLP by Nurul Shakila, Ahmad Zubir, Mohamad Aqib Haqmi, Abas, Ismail, N. A., Nor Azah, Mohd Ali, Mohd Hezri Fazalul, Rahiman, Ng, K. M., Mohd Nasir, Taib, Saiful Nizam, Tajuddin

“…This paper presents the modelling of agarwood oil (AO) significant compounds by different qualities using Scaled Conjugate Gradient (SCG) algorithm. This technique involved of data collection from Gas Chromatography-Mass Spectrometry (GC-MS) for compound extraction. …”
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Development Of Water Quality Index Prediction Model For Penang Rivers Using Artificial Neural Network by Mohd Hamdan, Eleena Yasmeen

“…For ANN prediction model development, four scenarios of the train-validate-test process to minimize model overfitting with 15 hidden nodes based on three built-in algorithms namely Levenberg-Marquart (LM), Bayesian Regularization (BR) and Scaled Conjugate Gradient (SCG) were created. …”
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