Search Results - deviation selection techniques

Determination the smoothing constant that minimizes mean absolute error and mean square deviation by Mamat, M., Prabowo, A., Tripena, A., Pratama, D.A., Susilo, I.G., Mukarromah, Z., Sukono, ., Bon, A.T.

“…This paper discusses the selection of the optimal smoothing constant value which minimizes the mean square error (MSE) and the mean absolute deviation (MAD). …”
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An empirical comparison of meta analysis models for continuous data with missing standard deviations by Nik Idris, Nik Ruzni, Saidin, Norraida

“…When the study-level standard deviations (SDs) are not completely reported or are “missing” selection of a meta analysis model should be done with more caution. …”
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Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares by Uraibi, Hassan Sami

“…In this respect, we propose to incorporate our proposed DRBLTS in the bootstrap model selection technique. We also proposed to use an alternative robust location and scale estimates which are less affected by outliers instead of using the classical mean and classical standard deviation. …”
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Deviation and mobility in female characters stimulated through ‘structure of feeling’ in selected American novels by Fejer, Azhar Noori

“…I also show the different genres and techniques the authors employ in order to come out with a developed female character. …”
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Stereo Vision Using Compensation Technique For Improvement Of Distance Measurement Accuracy For Robot Arm Applications by Eng, Swee Kheng

“…However, after compensation technique is performed, the mean and standard deviation of error for the z coordinates are reduced to -0.12 cm and 0.16 cm, respectively. …”
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Optimal Reactive Power Dispatch Solution by Loss Minimization Using Moth-Flame Optimization Technique by Rebecca Ng, Shin Mei, Mohd Herwan, Sulaiman, Zuriani, Mustaffa, Hamdan, Daniyal

“…The statisticalanalysis of this research illustrated that MFO is able to produce competitive results by yielding lowerpower loss and lower voltage deviation than the selected techniques from literature.…”
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Neural Network Model and Finite Element Simulation of Spring back in Plane-Strain Metallic Beam Bending by Abu Khadra, Fayiz Y. M.

“…This research utilizes computer generated D-optimal designs to select training examples for both metamodeling techniques so that a comparison between the two techniques can be considered as fair. …”
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On selection of models for continuos meta analysis data with incomplete variability measures by Nik Idris, Nik Ruzni, Sarudin, Norraida

“…When the study-level standard deviations (SDs) are not completely reported or are “missing” selection of a meta analysis model should be done with more caution. …”
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A study on solution chemistry and crystallization behavior of L-alanine in the presence of additives / Muhamad Fitri Othman by Othman, Muhamad Fitri

“…The binary system and ternary systems were found to deviate from the ideal system by negative deviations representing a high solute-solvent interaction. …”
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Investigation of the refined safety factor for berthing energy calculation by Kim, S.W., Lee, S.J., Kim, Y.T., Kim, D.K.

“…Moreover, the scenarios were selected efficiently by using a sampling technique. …”
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Electrode considerations, excitation methods and measurement techniques for electrical impedance tomography by Venkatratnam C., Farrukh N.

Feature selection in intrusion detection, state of the art: A review by Rais, H.M., Mehmood, T.

“…In this paper implementation of different feature selection techniques have been reviewed. Novel feature selection techniques have been developed due to its importance in network intrusion domain. …”
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Linear regression model selection based on robust bootstrapping technique by Uraibi, Hassan Sami, Midi, Habshah, Al-Talib, Bashar Abdul Aziz Majeed, Yousif, Jabar Hassan

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Mapping of the air pollution dispersion in the Klang Valley using remote sensing and GIS techniques / Suharti Ismail by Ismail, Suharti

“…This study addressed the Klang Valley as the study area and major pollutants (SO2, NO2, O3, CO and PM10) are used in selecting the image and results validation. The software packages used are mainly Erdas Imagine (digital data processing) and ArcGIS (Kriging technique). …”
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Real-time holographic backlighting positioning sensor for enhanced power coupling efficiency into selective launches in multimode fiber by Amphawan, Angela, Mishra, Vivekanand, Nisar, Kashif, Nedniyom, Benjaporn

“…This paper presents a qualitative, real-time backlighting positioning sensor for the alignment of an optical beam to a minutely deviated diffraction order axis to increase the power coupling efficiency into a multimode fiber in selective launches. …”
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Comparative investigation of bagging enhanced machine learning for early detection of HCV infections using class imbalance technique with feature selection by Tusher, Ekramul Haque, Mohd Arfian, Ismail, Akib, Abdullah, Gabralla, Lubna A., Ashraf Osman, Ibrahim, Hafizan, Mat Som, Muhammad Akmal, Remli

“…The performance of these ensemble methods is evaluated using metrics such as accuracy, recall, precision, F1 score, G-mean, balanced accuracy, cross-validation (CV), area under the curve (AUC), standard deviation, and error rate. Compared with previous studies, the Bagging k-NN model demonstrated superior performance under oversampling conditions, achieving 98.37% accuracy, 98.23% CV score, 97.67% precision, 97.93% recall, 98.18% selectivity, 97.79% F1 score, 98.06% balanced accuracy, 98.05% G-mean, a 1.63% error rate, 0.98 AUC, and a standard deviation of 0.192. …”
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Load case selection technique for combined modal finite element approach of high aspect ratio wing models by Nordin, Norzaima, Bohari, Baizura, Chandrasegaran, Thinesh, As’arry, Azizan, Harmin, Mohammad Yazdi

“…Therefore, this paper proposes a load case selection method as part of the combine modal finite element procedure, which initiates with normal mode selection and continues with loading profile selection technique, either using individual or combined modes. …”
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Enhancement of simultaneous network reconfiguration and DG sizing via Hamming dataset approach and firefly algorithm by Muhammad, Munir Azam, Mokhlis, Hazlie, Amin, Adil, Naidu, Kanendra, Franco, John Fredy, Wang, Li, Othman, Mohamadariff

“…Implicit radiality verification increases computational overhead and may lead to local optima. Whereas, improper selection of DG size poses direct consequences on the distribution network mainly on increased voltage deviation and power losses. …”
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Enhancing high-dimensional streaming data analysis: optimizing Online Feature Selection for handling drift using optimization technique and ensemble learning by Kamaru-Zaman, Ezzatul Akmal

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Natural Features Technique for Non-Contact Three Dimensional Craniofacial Anthropometry Using Stereophotogrammetry by Majid, Zulkepli, Chong, A, Setan, Halim, Ahmad, Anuar, Rajion, Zainul

“…The result shows that the craniofacial landmark measurement accuracy of 0.8mm with one standard deviation can be successfully achieved by the proposed technique.…”
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