Search Results - (( data selection method algorithm ) OR ( data evaluation case algorithm ))

Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

“…This technique with k = 10 has been used in this thesis to evaluate the proposed approach. CST was compared to other selected classification methods based on feature subset selection such as Induction of Decision Tree Algorithm (ID3), Base Learning Algorithm K-Nearest Nighbour Algorithm (k-NN) and NaYve Bay~sA lgorithm (NB). …”
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Hybrid Artificial Bees Colony algorithms for optimizing carbon nanotubes characteristics by Mohammad Jarrah, Mu'ath Ibrahim

“…Chemical Vapor Deposition (CVD) is the most efficient method for CNTs production.However,using CVD method encounters crucial issues such as customization,time and cost.Therefore,Response Surface Methodology (RSM) is proposed for modeling and the ABC-βHC is proposed for optimization purpose to address such issues.The selected CNTs characteristics are CNTs yield and quality represented by the ratio of the relative intensity of the D and G-bands (ID/IG).Six case studies are generated from collected dataset including four cases of CNTs yield and one case of ID/IG as single objective optimization problems,while the sixth case represents multi-objective problem.The input parameters of each case are a subset from the set of input parameters including reaction temperature,duration,carbon dioxide flow rate,methane partial pressure,catalyst loading,polymer weight and catalyst weight.The models for the first three case studies were mentioned in the original work.RSM is proposed to develop polynomial models for the output responses in the other three cases and to identi significant process parameters and interactions that could affect the CNTs output responses.The developed models are validated using t-test,correlation and pattern matching.The predictive results have a good agreement with the actual experimental data.The models are used as objective functions in optimization techniques.For multi-objective optimization,this study proposes Desirability Function Approach (DFA) to be integrated with other proposed algorithms to form hybrid techniques namely RSM-DFA,ABC-DFA and ABC-βHC-DFA.The proposed algorithms and other selected well-known algorithms are evaluated and compared on their CNTs yield and quality.The optimization results reveal that ABC-βHC and ABC-βHC-DFA obtained significant results in terms of success rate,required time,iterations,and function evaluations number compared to other well-known algorithms.Significantly,the optimization results from this study are better than the results from the original work of the collected dataset.…”
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Survey on Clustered Routing Protocols Adaptivity for Fire Incidents: Architecture Challenges, Data Losing, and Recommended Solutions by Abbas O.K., Abdullah F., Radzi N.A.M., Salman A.D., Abdulkadir S.J.

“…It evaluates the architectural challenges that caused network segmentations and data routing failures in the case of unexpected head node failures during high-stress events, particularly indoor fires. …”

Partitional clustering algorithms for highly similar and sparseness y-short tandem repeat data / Ali Seman by Seman, Ali

“…Six Y-STR data sets were used as a benchmark to evaluate the performances of the algorithm against the other eight partitional clustering algorithms. …”
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A regression test case selection and prioritization for object-oriented programs using dependency graph and genetic algorithm by Musa, Samaila, Md Sultan, Abu Bakar, Abd Ghani, Abdul Azim, Baharom, Salmi

“…The approach is based on optimization of selected test case from test suite T. The goal is to identify changes in a method's body due to data dependence, control dependence and dependent due to object relation such as inheritance and polymorphism, select the test cases based on affected statements and ordered them based on their fitness by using GA. …”
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Evaluating A New Adaptive Group Lasso Imputation Technique For Handling Missing Values In Compositional Data by Tian, Ying

“…Considering the impact of outliers on the accuracy of estimation, both simulation and case analysis are conducted to compare the proposed algorithm against four existing methods. …”
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Failure detection analysis of grid-connected photovoltaic system using an improved comparative based method / Fatin Azirah Mohd Shukor by Mohd Shukor, Fatin Azirah

“…The analysis was conducted using one-year historical data of 2019 from eight selected GCPV systems as the case studies. …”
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Development of priority oriented scheduling method to increase the efficiency and reliability for automotive job by Nojabaei, Seyedehfarzaneh

“…Also, to evaluate the proposed method of scheduling, a case study in an automotive manufacturing company (IKCO) is conducted. …”
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Development Of Construction Noise Prediction Method Using Deep Learning Model by Siew, Jun Teng

“…Based on the concept of a simple prediction chart, several ways for improvement, such as the duty cycle of the machinery and the receiver angle of 360°, can be included in the training noise data. In this project, thousands of deep learning models were trained and evaluated to select the best performance models for establishing a noise prediction model. …”
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Application of augmented bat algorithm with artificial neural network in forecasting river inflow in Malaysia by Wee W.J., Chong K.L., Ahmed A.N., Malek M.B.A., Huang Y.F., Sherif M., Elshafie A.

“…The findings of these evaluations highlighted that the adaptability of the proposed works would need detailed investigation because its performance differed from case to case. � 2022, The Author(s).…”

Empirical analysis of classifiers and feature selection techniques on mobile phone data activities by Harmaini, Fandi Husen, Mahmuddin, Massudi

“…This paper aims to analyze accuracy impact of selected feature selection techniques and classifiers that taken on mobile phone activity data and evaluate the method. …”
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A multi-objective portfolio selection model with fuzzy Value-at-Risk ratio by Wang, B., Li, Y., Wang, S., Watada, J.

“…Finally, the algorithm superiority is justified via comparing with existing solvers on benchmark problems, and the model effectiveness is exemplified by using three case studies on portfolio selection. …”
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A multi-objective portfolio selection model with fuzzy Value-at-Risk ratio by Wang, B., Li, Y., Wang, S., Watada, J.

“…Finally, the algorithm superiority is justified via comparing with existing solvers on benchmark problems, and the model effectiveness is exemplified by using three case studies on portfolio selection. …”
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The Use and Evaluation of Split-Window Techniques for NOAA/AVHRR Surface Temperature Extraction over Different Surface Covers: case study (Perak Tengah & Manjong) area, Malays... by Hassaballa A., Abdul-Haleem, Matori , Abdul Nasir

“…A reasonable negative relationship also was found between NDVI and Ts over the uniform vegetation covers, indicating the applicability/suitability of the so called “Triangle method”. The Use and Evaluation of Split-Window Techniques for NOAA/AVHRR Surface Temperature Extraction over Different Surface Covers: case study (Perak Tengah & Manjong) …”
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Using artificial intelligence search in solving the camera placement problem by Altahir, A.A., Asirvadam, V.S., Hamid, N.H.B., Sebastian, P.

“…Two case studies are used to evaluate those algorithms, and the camera placement problem is formulated as a coverage maximization problem. …”
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Liver segmentation on CT images using random walkers and fuzzy c-means for treatment planning and monitoring of tumors in liver cancer patients by Moghbel, Mehrdad

“…The proposed method is based on a hybrid method integrating random walkers algorithm with integrated priors and particle swarm optimized spatial fuzzy c-means (FCM) algorithm with level set method and AdaBoost classifier. …”
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elopment of Neural Network Model for Predicting Crucial Product Properties or Yield for Optimisation of Refinery Operation by Mohamad, Sharliza

“…The framework development for neural network modeling include aspects such as process understanding, data collection and division, input elements selection, data preprocessing, network type selection, design of network architecture, learning algorithm selection, network training, and network simulation using new data set. …”
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Spatial Data Mining Model For Landfill Sites Suitability Mapping Based On Neural Networks And Multivariate Analysis by Abujayyab, Sohaib K. M.

“…Hybrid neural network was utilized as an evaluation method to select the optimal selection method and optimal training algorithm. …”
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Optimized techniques for landslide detection and characteristics using LiDAR data by Mezaal, Mustafa Ridha

“…Also, six techniques: Ant Colony Optimization (ACO), Gain Ratio (GR), Particle Swarm Optimization (PSO) and Genetic Algorithm (GA), Random forest (RF), and Correlation-based Feature Selection (CFS) were used for the feature selection. …”
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Evaluation of deep learning algorithm for inflow forecasting: a case study of Durian Tunggal Reservoir, Peninsular Malaysia by Latif S.D., Ahmed A.N., Sathiamurthy E., Huang Y.F., El-Shafie A.