Search Results - (( java adaptation optimization algorithm ) OR ( knowledge utilization means algorithm ))

Parallel distributed genetic algorithm development based on microcontrollers framework by Krishnan P.S., Kiong T.S., Koh J.

Document clustering for knowledge discovery using nature-inspired algorithm by Mohammed, Athraa Jasim, Yusof, Yuhanis, Husni, Husniza

“…As the internet is overload with information, various knowledge based systems are now equipped with data analytics features that facilitate knowledge discovery.This includes the utilization of optimization algorithms that mimics the behavior of insects or animals.This paper presents an experiment on document clustering utilizing the Gravitation Firefly algorithm (GFA).The advantage of GFA is that clustering can be performed without a pre-defined value of k clusters.GFA determines the center of clusters by identifying documents with high force.Upon identification of the centers, clusters are created based on cosine similarity measurement.Experimental results demonstrated that GFA utilizing a random positioning of documents outperforms existing clustering algorithm such as Particles Swarm Optimization (PSO) and K-means.…”
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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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Comparison of clustering algorithms on air quality substances in Peninsular Malaysia / Sitti Sufiah Atirah Rosly, Balkiah Moktar and Muhamad Hasbullah Mohd Razali by Rosly, Sitti Sufiah Atirah, Moktar, Balkiah, Mohd Razali, Muhamad Hasbullah

“…Monthly data from 37 monitoring stations in Peninsular Malaysia from the year 2013 to 2015 were used in this study. K-Means (KM) clustering algorithm, Expectation Maximization (EM) clustering algorithm and Density Based (DB) clustering algorithm have been chosen as the techniques to analyze the cluster analysis by utilizing the Waikato Environment for Knowledge Analysis (WEKA) tools. …”
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Determining number of clusters using firefly algorithm with cluster merging for text clustering by Mohammed, Athraa Jasim, Yusof, Yuhanis, Husni, Husniza

“…Such a scenario requires a dynamic text clustering method that operates without initial knowledge on a data collection.In this paper, a dynamic text clustering that utilizes Firefly algorithm is introduced.The proposed, aFAmerge, clustering algorithm automatically groups text documents into the appropriate number of clusters based on the behavior of firefly and cluster merging process. …”
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Rule-based filtering algorithm for textual document by Jamil, Nurul Syafidah, Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

“…Improper filtration might cause terms that have similar meaning to be removed.Thus, to reduce the high-dimensionality of text, this study proposed a filtering algorithm that is able to filter the important terms from the pre-processed text and applied term weighting scheme to solve synonym problem which will help the selection of relevant term.The proposed filtering algorithm utilizes a keyword library that contained special terms which is developed to ensure that important terms are not eliminated during filtration process.The performance of the proposed filtering algorithm is compared with rough set attribute reduction (RSAR) and information retrieval (IR) approaches.From the experiment, the proposed filtering algorithm has outperformed both RSAR and IR in terms of extracted relevant terms.…”
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Fuzzy genetic algorithms for combinatorial optimisation problems by Varnamkhasti, Mohammad Jalali

“…Fuzzy Logic Controllers (FLCs) are considered as knowledge-based systems, incorporating human knowledge. …”
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Evaluation on rapid profiling with clustering algorithms for plantation stocks on Bursa Malaysia by Keng, Hoong Ng, Kok, Chin Khor

“…In this study, we utilized Expectation Maximization (EM), K-Means (KM), and Hierarchical Clustering (HC) algorithms to cluster the 38 plantation stocks listed on Bursa Malaysia using 14 financial ratios derived from the fundamental analysis.The clustering allows investors to profile each resulted cluster statistically and assists them in selecting stocks for their stock portfolios rapidly.The performance of each cluster was then assessed using 1-year stock price movement.The result showed that a cluster resulted from EM had a better profile and obtained a higher average capital gain as compared with the other clusters.…”
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Fuzzy Type-1 Triangular Membership Function Approximation Using Fuzzy C-Means by Azam, M.H., Hasan, M.H., Hassan, S., Abdulkadir, S.J.

“…Initially, the Fuzzy C-means algorithm is utilized to generate the parameters values of the Gaussian membership function. …”
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Cluster identification and separation in the growing self-organizing map: Application in protein sequence classification by Ahmad, N.

“…Growing self-organizing map (GSOM) has been introduced as an improvement to the self-organizing map (SOM) algorithm in clustering and knowledge discovery. Unlike the traditional SOM, GSOM has a dynamic structure which allows nodes to grow reflecting the knowledge discovered from the input data as learning progresses. …”
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Comparison of CPU damage prediction accuracy between certainty factor and forward chaining techniques by Tri Ginanjar Laksana, Ade Rahmat Iskandar, Wan Nooraishya Wan Ahmad

“…The suggested algorithm yields the mean accuracy of the certainty factor approach in diagnosing computer damage utilizing the constructed system. …”
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Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions by Saraswati, Galuh Wilujeng

“…The project has also implemented the optimization process onto the proposed ANFIS model through the hybrid of Genetic Algorithm on the fuzzy membership function of the ANFIS model. …”
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Research on the construction of an efficient and lightweight online detection method for tiny surface defects through model compression and knowledge distillation by Chen, Qipeng, Xiong, Qiaoqiao, Huang, Haisong, Tang, Saihong, Liu, Zhenghong

“…In response to the current issues of poor real-time performance, high computational costs, and excessive memory usage of object detection algorithms based on deep convolutional neural networks in embedded devices, a method for improving deep convolutional neural networks based on model compression and knowledge distillation is proposed. …”
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Tag cloud algorithm with the inclusion of personality traits by Supli, Ahmad Affandi, Shiratuddin, Norshuhada, Ab. Aziz, Azizi

“…Therefore, the main objective of this study is to make tag cloud algorithm with the inclusion of personality traits by adjusting two prominent visual features (color and shape) as an integration of layout.In addition, the utilization of RBS (rule bas e system) approach as artificial intelligent method is also taken into account to make knowledge base that stores the relationship between the proper personality elements and particular layout.This paper also discusses findings from satisfaction evaluation of prototyping, which comprises three dimensions facet: overall layout, color, and shape .The findings showed that the majority mean value for each dimension is categorized in agree scale (6-point), which indicates that respondents are satisfied with the tag cloud layout display generated by proposed algorithm.The findings suggest interface designers to be careful in selecting the appropriate tag clouds layout to be displayed for users with varying personality differences.…”
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Robust overlapping community detection in complex networks with graph convolutional networks and fuzzy C-means by Mohammed Al-Andoli, Mohammed Nasser, Che Ku Mohd, Che Ku Nuraini, Harny, Irianto, Jamil Alsayaydeh, Jamil Abedalrahim, Alwayle, Ibrahim M., Ahmed Abuhoureyah, Fahd Saad

“…In this paper, we propose an efficient method called GCNFCM, which utilizes Graph Convolutional Networks (GCNs), Fuzzy C-means (FCM), and the modularity Q algorithm for overlapping community detection. …”
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A coherent knowledge-driven deep learning model for idiomatic - aware sentiment analysis of unstructured text using Bert transformer by Bashar M. A., Tahayna

“…However, this task is not always trivial especially if the written text is ambiguous or includes figurative language that deviates the meaning of the words beyond their literal meaning rather to convey a complicated meaning. …”
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Biological-based semi-supervised clustering algorithm to improve gene function prediction by Kasim, Shahreen, Deris, Safaai, M. Othman, Razib, Hashim, Rathiah

“…Therefore, from this experiment, we can conclude that CluFA hadimproved the gene function prediction through the utilization of GO and gene expression values using the fuzzy c -meansclustering algorithm by cross referencing it with the latest SGD annotation.…”
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Modeling time series data using Genetic Algorithm based on Backpropagation Neural network by Haviluddin

“…Not many researchers have investigated the effects of optimizing both the topology structures and the parameters used in ANNs. This research utilizes a genetic algorithm (GA) to optimize the multi-layer FFNN performance and structure in modelling three datasets: network traffic, rainfall, and tourist. …”
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Modeling a problem solving approach through computational thinking for teaching programming / Zebel Al Tareq by Zebel , Al Tareq

“…Sorting algorithm as a concept for solving problems have been utilized to understand the effectiveness of the model in different teaching methods. …”
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Frequent Lexicographic Algorithm for Mining Association Rules by Mustapha, Norwati

“…The scale-up experiment showed that the proposed algorithm is more scalable than the other existing algorithms. …”
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