Search Results - (( new evaluation step algorithm ) OR ( data generation based algorithm ))

The new efficient and accurate attribute-oriented clustering algorithms for categorical data by Qin, Hongwu

“…Four real-life data sets obtained from University of California Irvine (UCI) machine learning repository and ten synthetically generated data sets are used to evaluate MGR and IG-ANMI algorithms, and other four algorithms are used to compare with these two algorithms. …”
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A new ant based rule extraction algorithm for web classification by Ku-Mahamud, Ku Ruhana, Saian, Rizauddin

“…Using Classifier-based attribute subset selection will reduce more attributes, but sacrifice the performance of the classifier.A hybrid ant colony optimization with simulated annealing algorithm to discover rules from data is proposed.The simulated annealing technique will minimize the problem of low quality discovered rule by an ant in a colony.The best rule for a colony will then be chosen and later the best rule among the colonies will be included in the rule set.The best rule for a colony will then be chosen and later the best rule among the colonies will be included in the rule set.The rule set is arranged in decreasing order of generation.Thirteen data sets which consist of discrete and continuous data were used to evaluate the performance of the proposed algorithm in terms of accuracy, number of rules and number of terms in the rules.Experimental results obtained from the proposed algorithm are comparable to the results of the Ant-Miner algorithm in terms of rule accuracy but are better in terms of rule simplicity.…”
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Development of an islanding detection scheme based on combination of slantlet transform and ridgelet probabilistic neural network in distributed generation by Ahmadipour, Masoud

“…In order to train Ridgelet probabilistic neural network, a modified differential evolution algorithm with new mutation phase, crossover process, and selection mechanism is introduced. …”
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Framework for stream clustering of trajectories based on temporal micro clustering technique by Abdulrazzaq, Musaab Riyadh

“…The clustering algorithm consists of two components: the temporal micro-clusters generation and the temporal micro clusters merging. …”
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Clustering of large time-series datasets using a multi-step approach / Saeed Reza Aghabozorgi Sahaf Yazdi by Yazdi, Saeed Reza Aghabozorgi Sahaf

“…It overcomes the limitations of conventional clustering algorithms in dealing with time-series data. In the first step of the model, data is pre-processed, represented by symbolic aggregate approximation, and grouped approximately by a novel approach. …”
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Automatic extraction of digital terrain model and Building Footprint from airborne LiDAR data using rule-based learning techniques by Jifroudi, Hamidreza Maskani

“…To achieve the first goal, the last reflection is separated from the LiDAR point cloud and the effective distance was calculated. In the next step, noise and roof errors were removed using KNN filter and a new network was created and re-evaluated based on the shortest distance in the LiDAR point cloud to create an integrated DTM. …”
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New optimization feature for the developed open cnc controller based on ISO 6983 and ISO 14649 by Obayes, Noor Hatem

“…This research aims to minimize tool path airtime during machining of input ISO codes via an ant colony optimization algorithm. A new optimized system was developed based on open architecture control (OAC) technology and interpreted STEP-NC (Standard for the Exchange of Product Model Data) programming approaches. …”
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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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Geospatial AI-based approach to assess the spatiotemporal suitability of onshore wind-solar farms in Iraq by Sachit, Mourtadha Sarhan Almushattat

“…In a separate third step, a new temporal criterion was developed based on temporal complementarity assessment between wind and solar resources. …”
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Sequence analysis and homology modeling of mouse TRPV5 and TRPV6 channels / Azreena Izzaty Abd Manan by Abd Manan, Azreena Izzaty

“…In homology modeling method, the steps involved including selection of protein template, multiple sequence alignment of mouse TRPV5 and TRPV6 sequence with the protein template sequence by using the selected algorithms, transmembrane domain prediction, model development and finally, model comparison and evaluation. …”
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Multistep forecasting for highly volatile data using new algorithm of Box-Jenkins and GARCH by Siti Roslindar, Yaziz, Roslinazairimah, Zakaria

“…This study is proposing a new algorithm of Box-Jenkins and GARCH (or BJ-G) in evaluating the multistep forecasting performance of the BJ-G model for highly volatile time series data. …”
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Application of data mining techniques for economic evaluation of air pollution impact and control by Lukman, Iing

“…Data sets for this research consist of two sets integration data of air quality data and macroeconomic data of the cross-country data of World Development Indicator 2003 (WDI 2003), and from www.nationmaster.com. …”
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A new reliable algorithm based on homotopy-perturbation method for power-law fin-type problems by Chowdhury, Md. Sazzad Hossien, Hassan, Talib Hashim

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DC-link capacitor voltage control for single-phase shunt active power filter with step size error cancellation in self-charging algorithm by Mohd Zainuri, Muhammad Ammirrul Atiqi, Mohd Radzi, Mohd Amran, Che Soh, Azura, Mariun, Norman, Abd Rahim, Nasrudin

“…This study presents an improved self-charging algorithm by introducing a new feature known as step size error cancellation for better performance of DC-link capacitor voltage control in single-phase shunt active power filter (SAPF). …”
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An online density-based clustering algorithm for data stream based on local optimal radius and cluster pruning by Islam, Md Kamrul

“…BOCEDS clusters the data stream in a single stage. The algorithm summarizes the data from data stream in micro-clusters. …”
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A new variable step size block backward differentiation formula for solving stiff initial value problems by Suleiman, Mohamed, Musa, Hamisu, Ismail, Fudziah, Senu, Norazak

“…A new block backward differentiation formula of order 4 with variable step size is formulated. …”
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Solving ump examination timetabling problem using dynamic exploration step counting hill climbing algorithm by Chang, Ling Shing

“…Then, the initial solution is improved using our enhanced algorithm called dynamic exploration step counting hill climbing (DESCHC). …”
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Enhanced Image View Synthesis Using Multistage Hybrid Median Filter For Stereo Images by Ali Hussein Aboali, Maged Yahya

“…Disparity depth map estimation of stereo matching algorithm is one of the most active research topics in computer vision.In the field of image processing,many existing stereo matching algorithms to obtain disparity depth map are developed and designed with low accuracy.To improve the accuracy of disparity depth map is quite challenging and difficult especially with uncontrolled dynamic environment.The accuracy is affected by many unwanted aspects including random noises,horizontal streaks,low texture,depth map non-edge preserving, occlusion,and depth discontinuities.Thus,this research proposed a new robust method of hybrid stereo matching algorithm with significant accuracy of computation.The thesis will present in detail the development,design, and analysis of performance on Multistage Hybrid Median Filter (MHMF).There are two main parts involved in our developed method which combined in two main stages.Stage 1 consists of the Sum of Absolute Differences (SAD) from Basic Block Matching (BBM) algorithm and the part of Scanline Optimization (SO) from Dynamic Programming (DP) algorithm.While,Stage 2 is the main core of our MHMF as a post-processing step which included segmentation,merging, and hybrid median filtering.The significant feature of the post-processing step is on its ability to handle efficiently the unwanted aspects obtained from the raw disparity depth map on the step of optimization.In order to remove and overcome the challenges unwanted aspects, the proposed MHMF has three stages of filtering process along with the developed approaches in Stage 2 of MHMF algorithm.There are two categories of evaluation performed on the obtained disparity depth map: subjective evaluation and objective evaluation.The objective evaluation involves the evaluation on Middlebury Stereo Vision system and evaluation using traditional methods such as Mean Square Errors (MSE),Peak to Signal Noise Ratio (PSNR) and Structural Similarity Index Metric (SSIM).Based on the results of the standard benchmarking datasets from Middlebury,the proposed algorithm is able to reduce errors of non-occluded and all errors respectively.While,the subjective evaluation is done for datasets captured from MV BLUE FOX camera using human's eyes perception.Based on the results,the proposed MHMF is able to obtain accurate results, specifically 69% and 71% of non-occluded and all errors for disparity depth map, and it outperformed some of the existing methods in the literature such as BBM and DP algorithms.…”
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PSAT : a pairwise test data generation tool based on simulated annealing algorithm by Goh, Ghee Hau

“…This research is about the research on developing a Pairwise Test Data Generation Tool based on Simulated Annealing (SA) algorithm which named as PSAT. …”
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Evaluating Bees Algorithm for Sequence-based T-way Testing Test Data Generation by M. H., Mohamed Zabil, Kamal Z., Zamli, K. C., Lim

“…Many t-way test data generation strategies have been proposed in the literature to generate optimized t-way test data. …”
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