Search Results - (( model validation _ algorithm ) OR ( subset selection based algorithm ))*

Modelling the yield loss of oil palm due to Ganoderma Basal Stem Rot disease by Assis Kamu

“…For estimation-post-selection approach, there were two subset selection algorithms were applied, namely backward stepwise subset selection and best-subset selection. …”
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Modelling the yield loss of oil palm due to ganoderma basal stem rot disease by Assis bin Kamu

“…For estimation-post-selection approach, there were two subset selection algorithms were applied, namely backward stepwise subset selection and best-subset selection. …”
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Short-term electricity price forecasting in deregulated electricity market based on enhanced artificial intelligence techniques / Alireza Pourdaryaei by Alireza , Pourdaryaei

“…The proposed feature selection technique comprises of Multi-objective Binary-valued Backtracking Search Algorithm (MOBBSA). …”
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Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi by Atefi, Kayvan

“…Experiments demonstrate and prove that the proposed EBPSO method produces better accuracy mining data and selecting subset of relevant features comparing other algorithms. …”
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

“…In the developed feature selection approach, multi-objective binary-valued backtracking search algorithm (MOBBSA) is used as an efficient evolutionary search algorithm to search within different combinations of input variables and selects the non-dominated feature subsets, which minimize simultaneously both the estimation error and the number of features. …”
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SVM for network anomaly detection using ACO feature subset by Mehmood, T., Rais, H.B.M.

“…Ant system has been used to remove those redundant and irrelevant features. The selected feature subset using ant system is then validated using support vector machine. …”
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Improved Manta Ray Foraging Optimizer-based SVM for Feature Selection Problems: A Medical Case Study by Got, Adel, Zouache, Djaafar, Moussaoui, Abdelouahab, Laith, Abualigah *, Alsayat, Ahmed

“…The proposed approach is validated and compared with four SVM-based algorithms over eight benchmarking datasets. …”
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Computational Technique for an Efficient Classification of Protein Sequences With Distance-Based Sequence Encoding Algorithm by Iqbal, M.J., Faye, I., Said, A.M.D., Samir, B.B.

“…A statistical metric-based feature selection algorithm is then adopted to identify the reduced set of features to represent the original feature space. …”
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Effective gene selection techniques for classification of gene expression data by Yeo, Lee Chin

“…Various k-means clustering algorithms and model-based clustering algorithms are proposed to group the genes. …”
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Towards a multispectral imaging system for spatial mapping of chemical composition in fresh-cut pineapple (Ananas comosus) by Mollazade, Kaveh, Hashim, Norhashila, Zude-Sasse, Manuela

“…Ranking and uncorrelatedness (based on ReliefF algorithm) and subset selection (based on CfsSubset algorithm) approaches were applied to find the most informative wavelengths in which bandpass optical filters or light sources are commercially available. …”
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Time series modeling of water level at Sulaiman Station, Klang River, Malaysia by Galavi, Hadi

“…A Subtractive Clustering Method was used in the fuzzy inference system to determine the optimal number of Membership Functions (MF) and rules. Using the cross validation method the best training subset is selected to train the ANFIS model based on that dataset. …”
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Intrusion Detection in Mobile Ad Hoc Networks Using Transductive Machine Learning Techniques by Farhan, Farhan Abdel-Fattah Ahmad

“…Feature selection is undertaken to select the relevant subsets of features to build an efficient prediction model and improve intrusion detection performance by removing irrelevant features. …”
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Heart disease prediction using artificial neural network with ADAM optimization and harmony search algorithm by Alyaa Ghazi Mohammed, Mohd Zakree Ahmad Nazri

“…Drawing from an extensive review of existing predictive models and cardiovascular health risk factors, this research proposes an enhanced ADAM optimization algorithm, integrated with advanced data processing and feature selection methodologies, to identify and refine key predictors for improved model performance. …”
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Enhanced dimensionality reduction methods for classifying malaria vector dataset using decision tree by Arowolo, Micheal Olaolu, Adebiyi, Marion Olubunmi, Adebiyi, Ayodele Ariyo

“…In this study, a novel optimized dimensionality reduction algorithm is proposed, by combining an optimized genetic algorithm with Principal Component Analysis and Independent Component Analysis (GA-O-PCA and GAO-ICA), which are used to identify an optimum subset and latent correlated features, respectively. …”
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Hybrid ANN and Artificial Cooperative Search Algorithm to Forecast Short-Term Electricity Price in De-Regulated Electricity Market by Pourdaryaei, Alireza, Mokhlis, Hazlie, Illias, Hazlee Azil, Kaboli, S. Hr. Aghay, Ahmad, Shameem, Ang, Swee Peng

“…Therefore, this research proposes a hybrid method for electricity price forecasting via artificial neural network (ANN) and artificial cooperative search algorithm (ACS). In parallel, a feature selection technique based on the combination of mutual information (MI) and neural network (NN) is developed in this study to select the input variables subsets, which have substantial impact on forecasting of electricity price. …”
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Aco-based feature selection algorithm for classification by Al-mazini, Hassan Fouad Abbas

“…The genetic method determines the final subset, automatically, based on the crossover and subset quality calculation. …”
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Hyperparameter tuned deep learning enabled intrusion detection on internet of everything environment by Ahmed Hamza, Manar, Hassan Abdalla Hashim, Aisha, G. Mohamed, Heba, S. Alotaibi, Saud, Mahgoub, Hany, S. Mehanna, Amal, Motwakel, Abdelwahed

“…In addition, Chaotic Local Search Whale Optimization Algorithm-based Feature Selection (CLSWOA-FS) technique is employed to choose the optimal feature subsets. …”
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Mixed-variable ant colony optimisation algorithm for feature subset selection and tuning support vector machine parameter by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…ACOMV-SVM algorithm is able to simultaneously tune SVM parameters and feature subset selection. …”
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Ant colony optimization based subset feature selection in speech processing: Constructing graphs with degree sequences by Rajesvary Rajoo R., Salam R.A.

Formulating new enhanced pattern classification algorithms based on ACO-SVM by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

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