Search Results - (( interval optimization method algorithm ) OR ( using classification modeling algorithm ))

Edge assisted crime prediction and evaluation framework for machine learning algorithms by Adhikary, Apurba, Murad, Saydul Akbar, Munir, Md Shirajum, Choong Seon, Hong Seong

“…Criminal risk is predicted using classification models for a particular time interval and place. …”
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Neural network approach for global solar irradiance prediction at extremely short-time-intervals using particle swarm optimization algorithm by Aljanad A., Tan N.M.L., Agelidis V.G., Shareef H.

The application of queuing theory model using the DSW Algorithm and the L-R Method to optimize customer flow at Pizza Hut / Anis Natasha Mohamad Nizam, Nurfatihah Nadirah Noor Azla... by Mohamad Nizam, Anis Natasha, Noor Azlan, Nurfatihah Nadirah, Fazli, Nur Izzati Aliah

“…This study aims to compare the behaviors of a queuing system at an order counter using the Fuzzy Queuing Model, which are the Dong, Shah, and Wong (DSW) Algorithm and the Left-Right (L-R) Method. One of the approximate methods that employs intervals at various a -cuts is the DSW Algorithm. …”
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Application of induced preorderings in score function-based method for solving decision-making with interval-valued fuzzy soft information by Ali, Mabruka, Kilicman, Adem, Khameneh, Azadeh Zahedi

“…Currently, there are three interval-valued fuzzy soft set-based decision-making algorithms in the literature. …”
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A novel hybrid classification model of genetic algorithms, modified k-Nearest Neighbor and developed backpropagation neural network by Salari, Nader, Shohaimi, Shamarina, Najafi, Farid, Nallappan, Meenakshii, Karishnarajah, Isthrinayagy

“…In the present study, the results of the implementation of a novel hybrid feature selection-classification model using the above mentioned methods are presented. …”
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Flood Routing in River Reaches Using a Three-Parameter Muskingum Model Coupled with an Improved Bat Algorithm by Farzin, Saeed, Singh, Vijay, Karami, Hojat, Farahani, Nazanin, Ehteram, Mohammad, Kisi, Ozgur, Allawi, Mohammed Falah, Mohd, Nuruol Syuhadaa, El-Shafie, Ahmed

“…Design of hydraulic structures, flood warning systems, evacuation measures, and traffic management require river flood routing. A common hydrologic method of flood routing is the Muskingum method. The present study attempted to develop a three-parameter Muskingum model considering lateral flow for flood routing, coupling with a new optimization algorithm namely, Improved Bat Algorithm (IBA). …”
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An improvement of BFGS by applying n-th section method for solving unconstrained optimization / Nurul Atikah Mohamed Ramli by Mohamed Ramli, Nurul Atikah

“…As in bisection method, this simple n-th section method divides each interval section with an even number of interval which is greater than two. …”
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Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model by Sulaiman, Md. Nasir, Mohamed, Raihani, Mustapha, Norwati, Zainudin, Muhammad Noorazlan Shah

“…EM and K-means clustering algorithms are used to cluster the multi-class classification attribute according to its relevance criteria and afterward, the clustered attributes are classified using an ensemble random forest classifier model. …”
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Incremental interval type-2 fuzzy clustering of data streams using single pass method by Qaiyum, S., Aziz, I., Hasan, M.H., Khan, A.I., Almalawi, A.

“…Data Streams create new challenges for fuzzy clustering algorithms, specifically Interval Type-2 Fuzzy C-Means (IT2FCM). …”
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An adaptive ant colony optimization algorithm for rule-based classification by Al-Behadili, Hayder Naser Khraibet

“…Various classification algorithms have been developed to produce classification models with high accuracy. …”
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Power production optimization of model-free wind farm using smoothed functional algorithm by R., Mok, M. A., Ahmad

“…Eventually, the obtained results have further revealed SFA based method as an efficacious optimization approach towards enhancing wind farm performance, in terms of a shorter convergence interval, greater precision and increased power maximization.…”
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Predicting breast cancer using ant colony optimisation / Siti Sarah Aqilah Che Ani by Che Ani, Siti Sarah Aqilah

“…This study implements a machine learning algorithm called Ant Colony Optimization (ACO) algorithm to develop an accurate classification model for predicting breast cancer cells. …”
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Comparative analysis of three approaches of antecedent part generation for an IT2 TSK FLS by Hassan, S., Khanesar, M.A., Jaafar, J., Khosravi, A.

“…In this paper, heuristic optimization approaches such as genetic algorithm and artificial bee colony are used to optimize the parameters of the antecedent part of interval type-2 fuzzy logic systems. …”
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Optimizing optimal path trace back for Smith-Waterman algorithm using structural modelling technique by Saliman, Nur Farah Ain

“…The optimizing of optimal path trace back system for Smith-Waterman algorithm using structural modelling techniques are presented in this paper. …”
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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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Classification model for water quality using machine learning techniques by Azilawati, Rozaimee, Azrul Amri, Jamal, Azwa, Abdul Aziz

“…In assessing the result, the Lazy model using K Star algorithm was the best classification model among the five models had the most outstanding accuracy of 86.67%. …”
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Scaled parallel iterative method for finding real roots of nonlinear equations by Chen, Chuei Yee, Ghazali, Abdul Hakim, Leong, Wah June

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Scaled parallel iterative method for finding real roots of nonlinear equations by Chuei, Yee Chen, Ghazali, Abdul Hakim, Wah, June Leong

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Classification of Diabetes Mellitus (DM) using Machine Learning Algorithms by Sirajun Noor, Noor Azmiya

“…Whereas for the German Frankfurt dataset, best DM classification model was found using Random Forest algorithm with an accuracy of 98.77%.…”
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Academic leadership bio-inspired classification model using negative selection algorithm by Jantan, Hamidah, Sa’dan, Siti ‘Aisyah, Che Azemi, Nur Hamizah Syafiqah

“…Several experiments were carried out by using different set of training and testing data-sets to evaluate the accuracy of the proposed model.As a result, the accuracy of the proposed model is considered excellent for academic leadership classification.For future work, in order to enhance the proposed bio-inspired classification model, a comparative study should be conducted using other established artificial immune system classification algorithms i.e. clonal selection and artificial immune network.…”
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