Search Results - (( developing function clustering algorithm ) OR ( learning object optimization algorithm ))

A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

“…The research starts with developing the hybrid deep learning model consisting of DNN and a K-Means Clustering Algorithm. …”
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Graph-Based Algorithm With Self-Weighted And Adaptive Neighbours Learning For Multi-View Clustering by He, Yanfang

“…To address the noise problem in multi-view data, this study enhances the gbs method and develops a new self-weighted graph multi-view clustering algorithm (swmcan). …”
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Modified spectral clustering algorithm for semisupervised face annotation modeling by Sheng, Gao You

“…Objectives included enhancing LPA accuracy, developing robust constraintbased clustering, and evaluating performance. …”
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Operational structural damage identification using de-noised modal feature in machine learning / Chen Shilei by Chen , Shilei

“…By integrating ISMA, both supervised and unsupervised machine learning algorithms were investigated to develop real-time damage identification schemes. …”
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A soft hierarchical algorithm for the clustering of multiple bioactive chemical compounds by Salim, Naomie, Shah, J. Z.

“…In this work a fuzzy hierarchical algorithm is developed which provides a mechanism not only to benefit from the fuzzy clustering process but also to get advantage of the multiple membership function of the fuzzy clustering. …”
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Clustering ensemble learning method based on incremental genetic algorithms by Ghaemi, Reza

“…So far, limited genetic-based clustering ensemble algorithms have been developed. …”
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The Parallel Fuzzy C-Median Clustering Algorithm Using Spark for the Big Data by Mallik, Moksud Alam, Zulkurnain, Nurul Fariza, Siddiqui, Sumrana, Sarkar, Rashel

“…Therefore, we develop a Parallel Fuzzy C-Median Clustering Algorithm Using Spark for Big Data that can handle large datasets while maintaining high accuracy and scalability. …”
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Reliability fuzzy clustering algorithm for wellness of elderly people by N. J., Mohd Jamal, Ku Muhammad Naim, Ku Khalif, Mohd Sham, Mohamad

“…Therefore, the implementation of z-numbers is taken into consideration, where it has more authority to describe the knowledge of human being and extensively used in uncertain information development. Thus, the objective of this paper is to propose a reliable fuzzy clustering algorithm using z-numbers. …”
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Clustering Methods For Cluster-Based Routing Protocols In Wireless Sensor Networks: Comparative Study by Hassan, Ali Abdul Hussian, Md Shah, Wahidah, Jabbar Mohammed, Ali Abdul, Othman, Mohd Fairuz Iskandar

“…These approaches of clustering algorithms whether Distributed, Centralized, or Hybrid are reviewed very well, since the most of clustering algorithms have been developed by many researches based on these approaches. …”
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Fuzzy clustering method and evaluation based on multi criteria decision making technique by Sameer, Fadhaa Othman

“…This proposed algorithm is developed based on heuristic method named modified binary particle swarm optimization (MBPSO) with kernel fuzzy clustering method as a fitness function. …”
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Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

“…There are many algorithm for analysing clustering each having its own method to do clustering. …”
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Efficient genetic partitioning-around-medoid algorithm for clustering by Garib, Sarmad Makki Mohammed

“…These algorithms mostly built upon the partitioning k-means clustering algorithm. …”
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Web based clustering tool using K-MEAN++ algorithm / Muhammad Nur Syazwanie Aznan by Aznan, Muhammad Nur Syazwanie Aznan

“…Which is why this project objective is to develop a web based clustering tool using K-MEAN++ algorithm. …”
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Cauchy Density-based Algorithm for VANETs Clustering in 3D Road Environments by AL-Obaidi, A.S., Jubair, M.A., Aziz, I.A., Ahmad, M.R., Mostafa, S.A., Mahdin, H., AL-Tickriti, A.T., Hassan, M.H.

“…In addition, a clustering algorithm that defines mobility vector and uses Cauchy-based density for enabling adding vehicles to their respective clusters. …”
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The implementation of z-numbers in fuzzy clustering algorithm for wellness of chronic kidney disease patients by N. J., Mohd Jamal, Ku Muhammad Naim, Ku Khalif, Mohd Sham, Mohamad

“…Thus, there are two objectives of this paper; (i) to propose a reliable fuzzy clustering algorithm using z-numbers and; (ii) to cluster the Chronic Kidney Disease (CKD) patients based on the selected indicators to identify which cluster the patients belongs to (Cluster 0, Cluster 1, Cluster 2, Cluster 3 or Cluster 4) based on the membership functions defined. …”
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Deep reinforcement learning approaches for multi-objective problem in Recommender Systems by Ee, Yeo Keat

“…The current major existing multi-objective recommendation approaches utilize collaborative filtering method as rating predictor to replenish the missing ratings and combined with evolutionary algorithm for only bi-objective optimization. …”
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Opposition-based learning simulated kalman filter for Numerical optimization problems by Mohd Falfazli, Mat Jusof

“…Simulated Kalman Filter (SKF) optimization algorithm is a population-based optimizer operated mainly based on Kalman filtering. …”
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Modeling time series data using Genetic Algorithm based on Backpropagation Neural network by Haviluddin

“…There are three objectives in this research. The first objective is to study the effects of varying the architecture designs and parameter values of the backpropagation neural network (BPNN) learning algorithm. …”
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A novel quasi-oppositional modified Jaya algorithm for multi-objective optimal power flow solution by Warid, Warid, Hizam, Hashim, Mariun, Norman, Abdul Wahab, Noor Izzri

“…This study introduces a novel meta-heuristic optimization algorithm known as quasi-oppositional modified Jaya (QOMJaya) to solve different multi-objective optimal power flow (MOOPF) problems. …”
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Automated bilateral negotiation with incomplete information in the e-marketplace. by Jazayeriy, Hamid

“…The reason is that, SRT algorithm is sensitive to the accuracy of the learned preferences while MGT algorithm can generate Pareto-optimal offers even with an approximation of the learned preferences.…”
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