Search Results - (( learning classification problem algorithm ) OR ( evolution optimization task algorithm ))

A New Quadratic Binary Harris Hawk Optimization For Feature Selection by Abdullah, Abdul Rahim, Too, Jing Wei, Mohd Saad, Norhashimah

“…Harris hawk optimization (HHO) is one of the recently proposed metaheuristic algorithms that has proven to be work more effectively in several challenging optimization tasks. …”
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A New Co-Evolution Binary Particle Swarm Optimization With Multiple Inertia Weight Strategy For Feature Selection by Too, Jing Wei, Abdullah, Abdul Rahim, Mohd Saad, Norhashimah

“…The proposed method is validated with ten benchmark datasets from UCI machine learning repository. To examine the effectiveness of proposed method, four recent and popular feature selection methods namely BPSO, genetic algorithm (GA), binary gravitational search algorithm (BGSA) and competitive binary grey wolf optimizer (CBGWO) are used in a performance comparison. …”
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Cloudlet deployment and task offloading in mobile edge computing using variable-length whale and differential evolution optimization and analytical hierarchical process for decisio... by Daba, Layth Muwafaq Abdulhussein

“…Enabling more optimality and adaptability to the dynamic nature of CDTO, we propose a novel Variable-Length multi-objective Whale optimization Integrated with Differential Evolution designated as VL-WIDE for joint cloudlet deployment and tasks offloading. …”
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Development of an improved GWO algorithm for solving optimal paths in complex vertical farms with multi-robot multi-tasking by Shen, Jiazheng, Hong, Tang Sai, Fan, Luxin, Zhao, Ruixin, Mohd Ariffin, Mohd Khairol Anuar, As’arry, Azizan

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Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition by Leong, Shi Xiang

“…The problems in applying unsupervised learning/clustering is that this method requires teacher during the classification process and it has to learn independently which may lead to poor classification. …”
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Accelerating learning performance of back propagation algorithm by using adaptive gain together with adaptive momentum and adaptive learning rate on classification problems by Abdul Hamid, Norhamreeza, Mohd Nawi, Nazri, Ghazali, Rozaida, Mohd Salleh, Mohd Najib

“…The back propagation (BP) algorithm is a very popular learning approach in feedforward multilayer perceptron networks. …”
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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

“…Meanwhile, Kmeans clustering algorithm has also been reported has widely known for solving most unsupervised classification problems. …”
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Nonlinear identification of a small scale unmanned helicopter using optimized NARX network with multiobjective differential evolution by Tijani, Ismaila B., Akmeliawati, Rini, Legowo, Ari, Budiyono, Agus

“…This study proposes a hybrid of conventional back propagation training algorithm for the NARX network and multiobjective differential evolution (MODE) algorithm for identification of a nonlinear model of an unmanned small scale helicopter from experimental flight data.The proposed hybrid algorithm was able to produce models with Pareto-optimal compromise between the design objectives. …”
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Grid-Based Classifier as a Replacement for Multiclass Classifier in a Supervised Non-Parametric Approach by Moheb Pour, Majid Reza

“…This method carries the advantages of the two previous methods in order to improve the classification tasks. The problem with the current lazy algorithms is that they learn quickly, but classify very slowly. …”
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Classification model for water quality using machine learning techniques by Azilawati, Rozaimee, Azrul Amri, Jamal, Azwa, Abdul Aziz

“…This article proposes a suitable classification model for classifying water quality based on the machine learning algorithms. …”
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Grid base classifier in comparison to nonparametric methods in multiclass classification by Moheb Pour, Majid Reza, Jantan, Adznan, Saripan, M. Iqbal

“…This method carries the advantages of the two previous methods in order to improve the classification tasks. The problem with the current lazy algorithms is that they learn quickly, but classify very slowly. …”
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A Hybrid of Ant Colony Optimization Algorithm and Simulated Annealing for Classification Rules by Rizauddin, Saian

“…The successful work on hybridization of ACO and SA algorithms has led to the improved learning ability of ACO for classification. …”
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Development of a Bioinspired optimization algorithm for the automatic generation of multiple distinct behaviors in simulated mobile robots by Hanafi Ahmad Hijazi, Patricia Anthony

“…A simulated Khepera robot is evolved by a Pareto-frontier Differential Evolution (POE) algorithm, and learned through a 3-layer feed-forward artificial neural network, attempting to simultaneously fulfill two conflicting objectives of maximizing robot phototaxis behavior while minimizing the neural network's hidden neurons by generating a Pareto optimal set of controllers. …”
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Heat exchanger network optimization using differential evolution with stream splitting by Thuy, N.T.P., Pendyala, R., Marneni, N.

“…This article introduces a new strategy for HEN optimization using differential evolution algorithm. …”
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A Comparison Between Levenberg-Marquardt (LM) Intelligent System And Bayesian Regularization (BR) Intelligent System For Flow Regime Classification by Sa'ad, Mohamad Iqbal

“…The purpose of this project is to study the performance, leaning time and, output of Levenberg-Marquardt (LM) intelligent system and Bayesian Regularization (BR) intelligent system through a classification problem. These studies will help in choosing the right training algorithm for classification problem involved. …”
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Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

“…One of the problems addressed by machine learning is data classification. …”
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An improve unsupervised discretization using optimization algorithms for classification problems by Mohamed, Rozlini, Samsudin, Noor Azah

“…This paper addresses the classification problem in machine learning focusing on predicting class labels for datasets with continuous features. …”
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An improve unsupervised discretization using optimization algorithms for classification problems by Mohamed, Rozlini, Samsudin, Noor Azah

“…This paper addresses the classification problem in machine learning, focusing on predicting class labels for datasets with continuous features. …”
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GPU-accelerated extractive multi-document text summarization using decomposition-based multi-objective differential evolution by Wahab, Muhammad Hafizul Hazmi, Abdul Hamid, Nor Asilah Wati, Subramaniam, Shamala, Latip, Rohaya, Othman, Mohamed

“…Multi-document text summarization is computationally intensive, mainly when employing complex optimization algorithms. The computational demands increase significantly due to the integration of complex optimization algorithms and the computationally expensive repair operator. …”
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Autism Spectrum Disorder Classification Using Deep Learning by Abdulrazak Yahya, Saleh, Lim Huey, Chern

“…The goal of this paper is to evaluate the deep learning algorithm for people placed in the Autism Spectrum Disorder (ASD) classification. …”
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