Search Results - (( java implication _ algorithm ) OR ( knowledge selection means algorithm ))

Algorithmic approaches in model selection of the air passengers flows data by Ismail, Suzilah, Yusof, Norhayati, Tuan Muda, Tuan Zalizam

“…Algorithm is an important element in any problem solving situation.In statistical modelling strategy, the algorithm provides a step by step process in model building, model testing, choosing the ‘best’ model and even forecasting using the chosen model.Tacit knowledge has contributed to the existence of a huge variability in manual modelling process especially between expert and non-expert modellers.Many algorithms (automated model selection) have been developed to bridge the gap either through single or multiple equation modelling.This study aims to evaluate the forecasting performances of several selected algorithms on air passengers flow data based on Root Mean Square Error (RMSE) and Geometric Root Mean Square Error (GRMSE).The findings show that multiple models selection performed well in one and two step-ahead forecast but was outperformed by single model in three step-ahead forecasts.…”
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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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Fuzzy genetic algorithms for combinatorial optimisation problems by Varnamkhasti, Mohammad Jalali

“…The female chromosome is selected by standard tournament selection while the male chromosome is selected based on the hamming distance from the selected female chromosome, fitness value or the active genes. …”
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Towards a better feature subset selection approach by Shiba, Omar A. A.

“…The selection of the optimal features subset and the classification has become an important issue in the data mining field.We propose a feature selection scheme based on slicing technique which was originally proposed for programming languages.The proposed approach called Case Slicing Technique (CST).Slicing means that we are interested in automatically obtaining that portion 'features' of the case responsible for specific parts of the solution of the case at hand.We show that our goal should be to eliminate the number of features by removing irrelevant once.Choosing a subset of the features may increase accuracy and reduce complexity of the acquired knowledge.Our experimental results indicate that the performance of CST as a method of feature subset selection is better than the performance of the other approaches which are RELIEF with Base Learning Algorithm (C4.5), RELIEF with K-Nearest Neighbour (K-NN), RELIEF with Induction of Decision Tree Algorithm (ID3) and RELIEF with Naïve Bayes (NB), which are mostly used in the feature selection task.…”
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MGR: An Information Theory Based Hierarchical Divisive Clustering Algorithm for Categorical Data by Hongwu, Qin, Ma, Xiuqin, Herawan, Tutut, Jasni, Mohamad Zain

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Comparative analysis of K-Means and K-Medoids for clustering exam questions / Nurul Zafirah Mokhtar by Mokhtar, Nurul Zafirah

“…The studies had found that k-Medoids produced higher accuracy result with 0.11% higher than k-Means. As a conclusion, with this type of data, k-Medoids algorithm had shown higher accuracy result rather than k-Means.…”
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Kernel and multi-class classifiers for multi-floor wlan localisation by Abd Rahman, Mohd Amiruddin

“…For fingerprint database optimisation, novel access point (AP) selection algorithms which are based on variant AP selection are investigated to improve computational accuracy compared to existing AP selection algorithms such as Max-Mean and InfoGain. …”
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Representing semantics of text by acquiring its canonical form by Taiye, Mohammed Ahmed, Kamaruddin, Siti Sakira, Ahmad, Farzana Kabir

“…Canonical form is a notion stating that related idea should have the same meaning representation. It is a notion that greatly simplifies task by dealing with a single meaning representation for a wide range of expression. …”
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Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things by Hadi, Ahmed Adnan

“…Here, the memory consumption can be reduced by enabling a feature selection algorithm that excludes nonrelevant features and preserves the relevant ones. the algorithm is developed based on the variable length of the PSO. …”
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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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Validation on an enhanced dendrite cell algorithm using statistical analysis by Mohamad Mohsin, Mohamad Farhan, Hamdan, Abdul Razak, Abu Bakar, Azuraliza, Abd Wahab, Mohd Helmy

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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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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

“…Firstly, data augmentation is employed in the preprocessing stage to increase the diversity of training samples, thereby improving the model’s robustness and generalization capability. The K-means++ clustering algorithm generates candidate bounding boxes, adapting to defects of different sizes and selecting finer features earlier. …”
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Modeling, Testing and Experimental Validation of Laser Machining Micro Quality Response by Artificial Neural Network by Sivarao, Subramonian

“…Therefore, prediction of laser machining cut quality, namely surface roughness was carried out using machine learning techniques based on Quick Back Propagation Algorithm using ANN. Experimentally observed responses were used to train, map and optimize the network algorithms before the best architecture was selected. …”
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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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Computational Thinking Through Unplugged Programming Activities : Exploring Students’ Learning Experiences by Lim, Bih Loong

“…However, the mean for post-test score is slightly higher than the mean for pre-test score. …”
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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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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.

Optimal Algorithms for Energy Storage Systems in Microgrid Applications: An Analytical Evaluation Towards Future Directions by Reza M.S., Rahman N., Wali S.B., Hannan M.A., Ker P.J., Rahman S.A., Muttaqi K.M.

A hybrid interpretable deep structure based on adaptive neuro‑fuzzy inference system, decision tree, and K‑means for intrusion detection by Jia, Lu, Yin Chai, Wang, Chee Siong, Teh, Xinjin, Li, Liping, Zhao, Fengrui, Wei

“…The proposed algorithm was trained, validated, and tested on the NSL-KDD (National security lab–knowledge discovery and data mining) dataset. …”
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