Search Results - (( variables classification using algorithm ) OR ( program implementation bees algorithm ))

Offline study on loss optimization in distribution networks using Artificial Bee Colony (ABC) algorithm: article / Deezex Noor Ainizaa Abdullah by Abdullah, Deezex Noor Ainizaa

“…This paper present offline study on loss optimization in distribution networks using Artificial Bee Colony (ABC) algorithm. The study involves the development of Artificial Bee Colony (ABC) algorithm to implement loss minimization in a distribution system. …”
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Offline study on loss optimization in distribution networks using Artificial Bee Colony (ABC) algorithm / Deezex Noor Ainizaa Abdullah by Abdullah, Deezex Noor Ainizaa

“…This paper present offline study on loss optimization in distribution networks using Artificial Bee Colony (ABC) algorithm. The study involves the development of Artificial Bee Colony (ABC) algorithm to implement loss minimization in a distribution system. …”
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Classification for large number of variables with two imbalanced groups by Ahmad Hakiim, Jamaluddin

“…This study proposed two algorithms of classification namely Algorithm 1 and Algorithm 2 which combine resampling, variable extraction, and classification procedure. …”
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Hybrid ACO and SVM algorithm for pattern classification by Alwan, Hiba Basim

“…Ant Colony Optimization (ACO) is a metaheuristic algorithm that can be used to solve a variety of combinatorial optimization problems. …”
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A study on solution of matrix riccati differential equations using ant colony programming and simulink / Mohd Zahurin Mohamed Kamali by Mohamed Kamali, Mohd Zahurin

“…In this thesis, we implement the modified ant colony programming (ACP) algorithm for solving the matrix Riccati differential equation (MRDE). …”
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Classification of tropical rainforest using different classification algorithm based on remote sensing imagery: A study of Gunung Basor by Intan Noradybah Md Rodi

“…Thehighest accuracy for classification map of Gunung Basor is by using maximum likelihood algorithm with an accuracy of 82.90%. …”
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Formulating new enhanced pattern classification algorithms based on ACO-SVM by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…ACO originally deals with discrete optimization problem.In applying ACO for solving SVM model selection problem which are continuous variables, there is a need to discretize the continuously value into discrete values.This discretization process would result in loss of some information and hence affects the classification accuracy and seeking time.In this algorithm we propose to solve SVM model selection problem using IACOR without the need to discretize continuous value for SVM.The second algorithm aims to simultaneously solve SVM model selection problem and selects a small number of features.SVM model selection and selection of suitable and small number of feature subsets must occur simultaneously because error produced from the feature subset selection phase will affect the values of SVM model selection and result in low classification accuracy.In this second algorithm we propose the use of IACOMV to simultaneously solve SVM model selection problem and features subset selection.Ten benchmark datasets were used to evaluate the proposed algorithms.Results showed that the proposed algorithms can enhance the classification accuracy with small size of features subset.…”
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Deterministic and stochastic inventory routing problems with backorders using artificial bee colony / Huda Zuhrah Ab Halim by Huda Zuhrah , Ab Halim

“…A new MILP for DSIRPB is formulated and used within the algorithm. The DSIRPB is modeled as stochastic dynamic programming and solved using hybrid rollout algorithm. …”
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Feature selection and model selection algorithm using incremental mixed variable ant colony optimization for support vector machine classifier by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…In order to enhance SVM performance, these problems must be solved simultaneously because error produced from the feature subset selection phase will affect the values of the SVM parameters and resulted in low classification accuracy.Most approaches related with solving SVM model selection problem will discretize the continuous value of SVM parameters which will influence its performance.Incremental Mixed Variable Ant Colony Optimization (IACOMV) has the ability to solve SVM model selection problem without discretising the continuous values and simultaneously solve the two problems.This paper presents an algorithm that integrates IACOMV and SVM.Ten datasets from UCI were used to evaluate the performance of the proposed algorithm.Results showed that the proposed algorithm can enhance the classification accuracy with small number of features.…”
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Study on numerical solution of a variable order fractional differential equation based on symmetric algorithm by Liu, Jingrui, Pan, Dongyang

“…A fully symmetric classification of the boundary value problem for a class of fractional differential equations with variable sequences is determined by using a fully symmetric differential sequence sorting algorithm. …”
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Machine learning classifications of multiple organ failures in a malaysian intensive care unit by Norliyana, Nor Hisham Shah, Normy Norfiza, Abdul Razak, Athirah, Abdul Razak, Asma’, Abu-Samah, Fatanah, M. Suhaimi, Ummu Kulthum, Jamaludin

“…This study aims to perform the classification of multiple organ failures using machine learning algorithms based on SOFA score. …”
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Gas Identi cation by Using a Cluster-k-Nearest-Neighbor by Brahim Belhaouari, samir

“…We find 98.7% of accuracy in the classification of 6 different types of Gas by using K-means cluster algorithm and we find almost the same by using the new clustering algorithm.…”
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Intelligent classification algorithms in enhancing the performance of support vector machine by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…Eight benchmark datasets from UCI were used in the experiments to validate the performance of the proposed algorithms. …”
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Machine Learning Classifications of Multiple Organ Failures in a Malaysian Intensive Care Unit by Shah N.N.H., Razak N.N.A., Razak A.A., Abu-Samah A., Suhaimi F.M., Jamaluddin U.

“…This study aims to perform the classification of multiple organ failures using machine learning algorithms based on SOFA score. …”

Computational intelligence of probabilistic simulation in demand side management for avoided utility cost improvisation in a generation operating system planning / Daw Saleh Sasi M... by Mohammed, Daw Saleh Sasi

“…In order produce a global optimal solution of AUC, the self-adaptive strategy was proposed to serve as a new mutation technique responsible to provide a new population for discrete artificial bee colony. The newly designed algorithm is termed as the discrete artificial bee colony associated with selfadaptive strategy (DABCSAS). …”
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Grey Wolf Optimizer for Solving Economic Dispatch Problems by Wong, Lo Ing, M. H., Sulaiman, Mohd Rusllim, Mohamed, Hong, Mee Song

“…In addition, the three main steps of hunting, searching for prey, encircling prey, and attacking prey, are implemented. The algorithm is then benchmarked on 20 generating units in economic dispatch, and the results are verified by a comparative study with Biogeography-based optimization (BBO), Lambda Iteration method (LI), Hopfield model based approach (HM), Cuckoo Search (CS), Firefly, Artificial Bee Colony (ABC), Neural Networks training by Artificial Bee Colony (ABCNN), Quadratic Programming (QP) and General Algebraic Modeling System (GAMS). …”
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Using fuzzy association rule mining in cancer classification by Mahmoodian, Sayed Hamid, Marhaban, Mohammad Hamiruce, Abdul Rahim, Raha, Rosli, Rozita, Saripan, M. Iqbal

“…In addition, creating a fuzzy classifier with high performance in classification that uses a subset of significant genes which have been selected by different types of gene selection methods is another goal of this study. …”
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Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification by Myaser, Jwan

“…Nevertheless, AC is not required for LCM if the original multi-spectral image is used. The last phase involves developing a new fusion algorithm using SVM and Fuzzy K-Means Clustering (FKM) algorithms for Sentinel 2 data to enhance LCM accuracy. …”
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Computational intelligence of probabilistic simulation in demand side management for avoided utility cost improvisation in a generation operating system planning / Daw Saleh Sasi M... by Sasi Mohamme, Daw Saleh

“…In order produce a global optimal solution of AUC, the self-adaptive strategy was proposed to serve as a new mutation technique responsible to provide a new population for discrete artificial bee colony. The newly designed algorithm is termed as the discrete artificial bee colony associated with selfadaptive strategy (DABCSAS). …”
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Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms by Rachmad, Iqbal, Tri Basuki, Kurniawan, Misinem, ., Edi Surya, Negara, Tata, Sutabri

“…The classification algorithm used in this research is the Convolutional Neural Network (CNN) algorithm. …”
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