Search Results - (( data classification modified algorithm ) OR ( variable optimization method algorithm ))

A hybrid-based modified adaptive fuzzy inference engine for pattern classification by Sayeed, Md. Shohel, Ramli, Abdul Rahman, Hossen, Md. Jakir, Samsudin, Khairulmizam, Rokhani, Fakhrul Zaman

“…A modified Apriori algorithm technique is utilized to reduce a minimal set of decision rules based on input output data set. …”
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Modified word representation vector based scalar weight for contextual text classification by Abbas Saliimi, Lokman

“…In addition, a contextual text classification experiment is conducted using benchmarked datasets to assess the performance of the modified word vectors in the targeted classification task. …”
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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

“…Among numerous artificial intelligence approaches, k-Nearest Neighbor algorithms, genetic algorithms, and artificial neural networks are considered as the most common and effective methods in classification problems in numerous studies. …”
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A modified weighted support vector machine (WSVM) to reduce noise data in classification problem by Mohd Dzulkifli, Syarizul Amri

“…Nowadays, the use of SVM is very perspective for the big data classification. SVM provides a global solution for data classification but SVM is highly sensitive to noise data and may not be effective when the level of noise data is high. …”
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A modified weighted support vector machine (WSVM) to reduce noise data in classification problem by Mohd Dzulkifli, Syarizul Amri

“…Nowadays, the use of SVM is very perspective for the big data classification. SVM provides a global solution for data classification but SVM is highly sensitive to noise data and may not be effective when the level of noise data is high. …”
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The Bacterial Foraging Optimisation Algorithm using Prototype Selection and Prototype Generation for Data Classification by Faizol, Bin Mohd Suria

“…Thus, this study aims to adopt and modify the BFOA into Instance Selection (IS) classifier by manipulating its global search capability and high convergence rate for data classification problem. …”
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Mutable composite firefly algorithm for gene selection in microarray based cancer classification by Fajila, Mohamed Nisper Fathima

“…A computational approach for gene selection based on microarray data analysis has been applied in many cancer classification problems. …”
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Optimization of PID parameters for hydraulic positioning system utilizing variable weight Grey-Taguchi and particle swarm optimization by Nur Iffah, Mohamed Azmi

“…Particle swarm optimization algorithm (PSO) is one of the artificial intelligence methods. …”
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Optimization of PID Parameters Utilizing Variable Weight Grey-Taguchi Method and Particle Swarm Optimization by Nur Iffah, Mohamed Azmi, Kamal Arifin, Mat Piah, Wan Azhar, Wan Yusoff, F. R. M., Romlay

“…Particle swarm optimization algorithm (PSO) is one of the artificial intelligence methods. …”
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Study Of Modified Training Algorithm For Optimized Convergence Speed Of Neural Network by Kang, Miew How

“…Two modified algorithms are proposed in this research, which are mixture of the momentum algorithm with different learning rate algorithms. …”
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Automated classification of blasts in acute leukemia blood samples using HMLP network by Harun, N. H., Mashor, M.Y., Abdul Nasir, A.S., Rosline, H.

“…This paper presents a study on classification of blasts in acute leukemia blood samples using artificial neural network.In acute leukemia there are two major forms that are acute myelogenous leukemia (AML) and acute lymphocytic leukemia (ALL).Six morphological features have been extracted from acute leukemia blood images and used as neural network inputs for the classification.Hybrid Multilayer Perceptron (HMLP) neural network was used to perform the classification task.The Hybrid Multilayer Perceptron(HMLP) neural network is trained using modified RPE(MRPE) training algorithm for 1474 data samples.The Hybrid Multilayer Perceptron (HMLP) neural network produces 97.04% performance accuracy.The result indicates the promising capabilities and abilities of the Hybrid Multilayer Perceptron (HMLP) neural network using modified RPE (MRPE) training algorithm for classifying and distinguishing the blasts from acute leukemia blood samples.…”
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Enhanced Flipping Technique to Reduce Variability in Image Steganography by Kamil S., Abdullah S.N.H.S., Hasan M.K., Bohani F.A.

Optimization Of Bar Linkage By Using Genetic Algorithms by Ramasamy, Mugilan

“…This thesis presents the method of using simple Genetic Algorithms (GAs) in optimizing the size of bar linkage with discrete design variables and continues design variables. …”
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Optimizing the placement of fire department in Kulim using greedy heuristic and simplex method / Muhammad Abu Syah Mohd Suzaly by Mohd Suzaly, Muhammad Abu Syah

“…The first method is greedy heuristic method. Greedy heuristics is a type of optimization algorithm that makes decisions based on locally optimal solutions. …”
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Predicting Customer Buying Decisions for Online Shopping with Unbalanced Data Set by Yap, Chau Tean

“…Data pre-processing on the data set may improve the classification results. …”
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Mine blast algorithm for optimization of truss structures with discrete variables by Sadollah, Ali, Bahreininejad, A., Eskandar, Hadi, Abd Shukor, Mohd Hamdi

“…In this study a novel optimization method is presented, the so called mine blast algorithm (MBA). …”
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Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification by Myaser, Jwan

“…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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Using Metaheuristics Algorithms (MHAs) to Optimize Water Supply Operation in Reservoirs: a Review by Almubaidin M.A.A., Ahmed A.N., Sidek L.B.M., Elshafie A.

Logistic regression methods for classification of imbalanced data sets by Santi Puteri Rahayu, -

“…Classification of imbalanced data sets is one of the important researches in Data Mining community, since the data sets in many real-world problems mostly are imbalanced class distribution. …”
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A firefly algorithm based hybrid method for structural topology optimization by Gebremedhen, H.S., Woldemichael, D.E., Hashim, F.M.

“…In this paper, a firefly algorithm based hybrid algorithm through retaining global convergence of firefly algorithm and ability to generate connected topologies of optimality criteria (OC) method is proposed as an alternative method to solve stress-based topology optimization problems. …”
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