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Integrated bisect K-means and firefly algorithm for hierarchical text clustering by Mohammed, Athraa Jasim, Yusof, Yuhanis, Husni, Husniza

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Comparative Analysis on Blood Cell Image Segmentation by Muda, TZT, Salam, RA

Improved clustering using robust and classical principal component by Hassn, Ahmed Kadom

“…The classical k-means algorithm and the k-means by PCA algorithm are very sensitive to the presence of outlier. …”
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Augmented model based double iterative loop techniques for integrated system optimisation and parameter estimation of large scale industrial processes by Normah Abdullah, Brdys, M.A., Roberts, P.D.

“…This means that the algorithms use available information from the real process efficiently and a significant reduction in set-point alterations to real subprocesses is achieved. …”
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Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition by Leong, Shi Xiang

“…Phase 1 is mainly to evaluate the performance of clustering algorithm (K-Means and FCM). Phase 2 is to study the performance of proposed integration system which using the data clustered to be used as train data for Naïve Bayes classifier. …”
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Comparative analysis on blood cell image segmentation by Tuan Muda, Tuan Zalizam, Abdul Salam, Rosalina

“…K-means has been enhanced by integrating Median-cut algorithm to further improve the segmentation process.The proposed integrated method has shown a significant improvement in the number of selected regions.…”
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Intelligent segmentation of fruit images using an integrated thresholding and adaptive K-means method (TSNKM) by Hambali, Hamirul ’Aini, Syed Abdullah, Sharifah Lailee, Jamil, Nursuriati, Harun, Hazaruddin

“…Currently, there are several segmentation techniques which have been used in object identification such as thresholding and clustering techniques.However, the conventional techniques have difficulties in segmenting fruit images which captured under natural illumination due to the existence of non-uniform illumination on the object surface.The presence of different illuminations influences the appearance of the interest objects and thus misleads the object analysis.Therefore, this research has produced an innovative segmentation algorithm for fruit images which is able to increase the segmentation accuracy.The developed algorithm is an integration of modified thresholding and adaptive K-means method.The integration of both methods is required to increase the segmentation accuracy for fruits images with different surface colour.The results showed that the innovative method is able to segment the fruits images with high accuracy value.…”
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Real time monitoring and controlling using Petri net algorithm for batch process plant / Mohamad Shaiful Osman by Osman, Mohamad Shaiful

“…This research is made for a system with fully integrated facilities for analyzing , monitoring and controlling of batch plant based on graph theory, batch modelling by means of Petri net algorithm and theory, control and configuration of SCADA system. …”
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Image segmentation using an adaptive clustering technique for the detection of acute leukemia blood cells images by Jabar F.H.A., Ismail W., Salam R.A., Hassan R.

The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Alzaeemi, Shehab Abdulhabib, Tay, Kim Gaik, Huong, Audrey, Sathasivam, Saratha, Majahar Ali, Majid Khan

“…With the use of SRBFNN-2SAT, a training method based on these algorithms has been presented, then training has been compared among algorithms, which were applied in Microsoft Visual C++ software using multiple metrics of performance, including Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), Systematic Error (SD), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). …”
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Artificial intelligent integrated into sun-tracking system to enhance the accuracy, reliability and long-term performance in solar energy harnessing by Tan, Jun You

“…The proposed AI algorithm integrates two deep learning models which are object detection algorithm and reinforcement learning. …”
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Image Segmentation Using an Adaptive Clustering Technique for the Detection of Acute Leukemia Blood Cells Images by Jabar, FHA, Ismail, W, Salam, RA, Hassan, R

“…This paper aims to segment the blood cell images of patients suffering from acute leukemia using an adaptive K-Means clustering together with mean shift algorithm. …”

Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

“…With the use of SRBFNN-2SAT, a training method based on these algorithms has been presented, then training has been compared among algorithms, which were applied in Microsoft Visual C++ software using multiple metrics of performance, including Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), Systematic Error (SD), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majid Khan bin Majahar Ali, Majid Khan bin Majahar Ali

“…With the use of SRBFNN-2SAT, a training method based on these algorithms has been presented, then training has been compared among algorithms, which were applied in Microsoft Visual C++ software using multiple metrics of performance, including Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), Systematic Error (SD), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

“…With the use of SRBFNN-2SAT, a training method based on these algorithms has been presented, then training has been compared among algorithms, which were applied in Microsoft Visual C++ software using multiple metrics of performance, including Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), Systematic Error (SD), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

“…With the use of SRBFNN-2SAT, a training method based on these algorithms has been presented, then training has been compared among algorithms, which were applied in Microsoft Visual C++ software using multiple metrics of performance, including Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), Systematic Error (SD), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Alzaeemi, Shehab Abdulhabib, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

“…With the use of SRBFNN-2SAT, a training method based on these algorithms has been presented, then training has been compared among algorithms, which were applied in Microsoft Visual C++ software using multiple metrics of performance, including Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), Systematic Error (SD), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). …”
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Real time nonlinear filtered-x lms algorithm for active noise control by Sahib, Mouayad Abdulredha

“…The performance of these algorithms is usually compared with the standard linear filtered-x least mean square (FXLMS) algorithm. …”
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Image Segmentation using Enhanced K-means Clustering with Hybrid Image Filtering for Acute Leukemia Blood Cells Microscopic Images by Farah Hanim Bt Abd Jabar