Search Results - (( java implementation means algorithm ) OR ( using function machine algorithm ))

A web-based implementation of k-means algorithms by Lee, Quan

“…The K-means algorithm has been around for over a century. …”
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Comparison of Search Algorithms in Javanese-Indonesian Dictionary Application by Yana Aditia, Gerhana, Nur, Lukman, Arief Fatchul, Huda, Cecep Nurul, Alam, Undang, Syaripudin, Devi, Novitasari

“…This study aims to compare the performance of Boyer-Moore, Knuth morris pratt, and Horspool algorithms in searching for the meaning of words in the Java-Indonesian dictionary search application in terms of accuracy and processing time. …”
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Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly by Zulkifly, Ahmad Zuladzlan

“…This project will use fuzzy k-means clustering algorithm to cluster the data because it is easy to implement and have many advantages. …”
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Binary Coati Optimization Algorithm- Multi- Kernel Least Square Support Vector Machine-Extreme Learning Machine Model (BCOA-MKLSSVM-ELM): A New Hybrid Machine Learning Model for Pr... by Sammen S.S., Ehteram M., Sheikh Khozani Z., Sidek L.M.

“…For water level prediction, lagged rainfall and water level are used. In this study, we used extreme learning machine (ELM)-multi-kernel least square support vector machine (ELM-MKLSSVM), extreme learning machine (ELM)-LSSVM-polynomial kernel function (PKF) (ELM-LSSVM-PKF), ELM-LSSVM-radial basis kernel function (RBF) (ELM-LSSVM-RBF), ELM-LSSVM-Linear Kernel function (LKF), ELM, and MKLSSVM models to predict water level. …”

Landslide risk zoning using support vector machine algorithm by Ghiasi V., Pauzi N.I.M., Karimi S., Yousefi M.

“…The weighted maps were then combined using the support vector machine algorithm. For the training and testing of the machine, 81 slippery ground points and 81 non-sliding points were used. …”

Biometrics electronic purse by Abdul Rahman, Abdul Wahab, Eng, Chong Tan, S., M. Heng

“…This paper looked into using biometrics as a mean of authentication, thus requiring a new generation of Smart Card technology to be implemented in banking and multiple applications environment. …”
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Development Of Generative Computer-Aided Process Planning System For Lathe Machining by Zubair, Ahmad Faiz

“…Furthermore, to minimize unit production cost, machining parameters including cutting speed (CS), feed rate (f) and depth of cut (d) were optimized for regular form surfaces by using firefly algorithm (FA). …”
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Movie recommendation system / Najwa Syamimie Hasnu by Hasnu, Najwa Syamimie

“…PHPMyAdmin is used to store the dataset and also acts as a database for user information. The algorithm chosen was implemented using Java Programming language and was tested using Root Means Square Error (RMSE) formula.…”
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Optimization machining parameters in pocket milling using genetic algorithm and mastercam by Abdullah, Haslina, Isa, Nurshafinaz, Zakaria, Mohamad Shukri

“…Mastercam software has been used to verify the algorithm's results by applying the optimum parameter generated by GA in the Mastercam. …”
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Support directional shifting vector: A direction based machine learning classifier by Kowsher, Md., Hossen, Imran, Tahabilder, Anik, Prottasha, Nusrat Jahan, Habib, Kaiser, Zafril Rizal, M Azmi

“…The positional error of the linear function has been modelled as a loss function which is iteratively optimized using the gradient descent algorithm. …”
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Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

“…This project proposed a two color segmentation techniques such as K-means and Fuzzy C-means clustering algorithm that are accurately segment the desired images, which have the same color as the pre-selected pixels with background subtraction. …”
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Different mutation and crossover set of genetic programming in an automated machine learning by Masrom, S., Mohamad, M., Hatim, S.M., Baharun, N., Omar, N., Abd. Rahman, A.S.

“…The function of Genetic Programming is to optimize the best combination of solutions from the possible pipelines of machine learning modelling, including selection of algorithms and parameters optimization of the selected algorithm. …”
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Different mutation and crossover set of genetic programming in an automated machine learning by Masrom, S., Mohamad, M., Hatim, S.M., Baharun, N., Omar, N., Abd. Rahman, A.S.

“…The function of Genetic Programming is to optimize the best combination of solutions from the possible pipelines of machine learning modelling, including selection of algorithms and parameters optimization of the selected algorithm. …”
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Predictive modelling of machining parameters of S45C mild steel by Abbas, Adnan Jameel

“…The PSO1 algorithm which used first main temperature objective function gives the best roughness value (0.52 μm) compared with other algorithms, followed by the AIS2 and PSO2 that give (0.86 μm). …”
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Extreme learning machine model for state-of-charge estimation of lithium-ion battery using gravitational search algorithm by Hossain Lipu M.S., Hannan M.A., Hussain A., Saad M.H., Ayob A., Uddin M.N.

Interaction effect of process parameters and Pd-electrocatalyst in formic acid electro-oxidation for fuel cell applications: Implementing supervised machine learning algorithms by Hossain S.K.S., Ali S.S., Rushd S., Ayodele B.V., Cheng C.K.

An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM) by Shamim, Akhtar

“…The scope of this study is tri folded, First, an exhaustive and parametric comparative study on a wide variety of machine learning algorithms is presented to evaluate the performance of machine learning algorithms in energy load prediction. …”
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A hybrid novel SVM model for predicting CO2 emissions using Multiobjective Seagull Optimization by Ehteram M., Sammen S.S., Panahi F., Sidek L.M.

Integrated Features by Administering the Support Vector Machine of Translational Initiations Sites in Alternative Polymorphic Context by Nanna Suryana, Herman, Burairah, Hussin

“…The applied discriminative approach is used to learn about some discriminant functions of samples that have been labelled as positive or negative. …”
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To study the multi-objective optimization of EDM using genetic algorithm by Fairuz, Idris

“…In the process of the study, the second- order mathematical model has been create as a fitness function using MATLAB software to generate multi-objective optimization responses using Genetic Algorithms, peak current, pulse-on time, pulse-off time and servo voltage are act as input of parameter setting. …”
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