Search Results - (( developing interactive pollination algorithm ) OR ( java classification learning algorithm ))

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  1. 1
    An elitist-flower pollination-based strategy for constructing sequence and sequence-less t-way test suite

    An elitist-flower pollination-based strategy for constructing sequence and sequence-less t-way test suite by Abdullah, Nasser, Kamal Z., Zamli, Alsewari, Abdulrahman A., Ahmed, Bestoun S.

    Published 2018
    “…In line with the upcoming of a new field called search-based software engineering (SBSE), many newly developed t-way strategies adopting meta-heuristic algorithms can be seen in the literature for constructing interaction test suite (such as simulated annealing (SA), genetic algorithm (GA), ant colony optimisation algorithm (ACO), particle swarm optimisation (PSO), harmony search (HS) and cuckoo search (CS). …”
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  2. 2
    Sequence and sequence-less t-way test suite generation strategy based on the elitist flower pollination algorithm

    Sequence and sequence-less t-way test suite generation strategy based on the elitist flower pollination algorithm by Mohammed Abdullah, Abdullah Nasser

    Published 2018
    “…If t-way strategies are to be adopted in such a system, there is also a need to support test data generation based on sequence of interactions. Addressing these aforementioned issues and complementing the existing sequence based strategies such as t-SEQ, Sequence Covering Array Generator and Bee Algorithm, this thesis presents a unified strategy based on the new meta-heuristic algorithm, called the Elitist Flower Pollination Algorithm (eFPA). …”
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  3. 3
    Hybrid flower pollination algorithm strategies for t-way test suite generation

    Hybrid flower pollination algorithm strategies for t-way test suite generation by Abdullah, Nasser, Kamal Z., Zamli, Alsewari, Abdulrahman A., Ahmed, Bestoun S.

    Published 2018
    “…Consequently, many useful meta-heuristic algorithms have been developed on the basis of the implementation of t-way strategies (where t indicates the interaction strength). …”
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  4. 4
    An ensemble learning method for spam email detection system based on metaheuristic algorithms

    An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

    Published 2015
    “…Recently, various techniques based on different algorithms have been developed. However, the classification accuracy and computational cost are not satisfied. …”
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  5. 5
    Sequence and sequence-less T-way test suite generation strategy based on flower pollination algorithm

    Sequence and sequence-less T-way test suite generation strategy based on flower pollination algorithm by Abdullah, Nasser, Hujainah, Fadhl, Alsewari, Abdulrahman A., Kamal Z., Zamli

    Published 2015
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  6. 6
    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde

    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

    Published 2022
    “…This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
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  7. 7
    Performance properties optimization of triaxial ceramic-palm oil fuel ash by employing Taguchi design and flower pollination algorithm

    Performance properties optimization of triaxial ceramic-palm oil fuel ash by employing Taguchi design and flower pollination algorithm by Zainudin, Azlan

    Published 2018
    “…In the meantime, both linear and interaction approach of FPA developed following optimal parameters: 5 wt.% of ground POFA, pressed at 4 t, and sintered at 1200 °C for 300 min of soaking time. …”
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  8. 8
    Face classification for three major ethnic of Orang Asli using Back Propagation Neural Network / Nor Intan Shafini Nasaruddin

    Face classification for three major ethnic of Orang Asli using Back Propagation Neural Network / Nor Intan Shafini Nasaruddin by Nasaruddin, Nor Intan Shafini

    Published 2012
    “…The image classification prototype is developed by using JAVA programming language which is based on supervised learning algorithm, Backpropagation Neural Network. …”
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  9. 9
    A Unified Strategy for Sequence and Sequence-less T-way Test Suite Generation

    A Unified Strategy for Sequence and Sequence-less T-way Test Suite Generation by Abdullah, Nasser, Hujainah, Fadhl, Alsewari, Abdulrahman A., Kamal Z., Zamli

    Published 2016
    “…In the last 20 years, many useful t-way strategies (where t indicates the interaction strength) have been developed to help generate test suite for detecting fault due to interaction of inputs. …”
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  10. 10
    Development Of Machine Learning User Interface For Pump Diagnostics

    Development Of Machine Learning User Interface For Pump Diagnostics by Lee, Zhao Yang

    Published 2022
    “…The features extracted of time domain and frequency domain in vibration and acoustic will use as database of a Support Vector Machine (SVM) algorithms by using MATLAB R2021a. The result from the SVM algorithms will be used as database for the machine learning in Microsoft Azure. …”
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  11. 11
    Landslide Susceptibility Mapping with Stacking Ensemble Machine Learning

    Landslide Susceptibility Mapping with Stacking Ensemble Machine Learning by Solihin M.I., Yanto, Hayder G., Maarif H.A.-Q.

    Published 2024
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  12. 12
    Object-Oriented Programming semantics representation utilizing agents

    Object-Oriented Programming semantics representation utilizing agents by Mohd Aris, Teh Noranis

    Published 2011
    “…Generally, these source codes go through the preprocessing, comparison, extraction, generate program semantics and classification processes. A formal algorithm that can be applied to any two related Java-based source codes examples is invented to generate the semantics of these source codes. …”
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  13. 13
    Features selection for intrusion detection system using hybridize PSO-SVM

    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…The results reveal that the proposed hybrid algorithm is capable of achieving classification accuracy values of (95.82 % and 97.68 %), detection rates values of (95.8 % and 99.3 %) and false alarm rates values of (0.083 % and 0.045 %) on both KDD CUP 99 and NSL KDD. …”
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  14. 14
    Assessing optimization based strategies for t-way test suite generation: The case for flower-based strategy

    Assessing optimization based strategies for t-way test suite generation: The case for flower-based strategy by Abdullah, Nasser, Sariera, Yazan A., Alsewari, Abdulrahman A., Kamal Z., Zamli

    Published 2016
    “…Addressing this issue, the adoption of t-way testing (where t indicates the interaction strength) has come into the limelight. In order to summarize the achievements so far and facilitate future development, the main focus of this paper is, first, to present a critical comparison of adoption optimization algorithms (OA) as a basis of the t-way test suite generation strategy and, second, to propose a new t-way strategy based on Flower Pollination Algorithm, called Flower Strategy (FS). …”
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  15. 15
    Hyper-heuristic strategy for input-output-based interaction testing

    Hyper-heuristic strategy for input-output-based interaction testing by Din, Fakhrud, Kamal Zuhairi, Zamli

    Published 2022
    “…Classical test case design strategies, however, do not sufficiently include support for exploration of faults due to interaction between parameter values. New strategies known as t-way strategies (where t expresses interaction strength) have been developed for finding interaction faults. …”
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  16. 16
    Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions

    Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions by Saraswati, Galuh Wilujeng

    Published 2017
    “…Future work should be focusing on data collection of the E-Nose sensors and the improvement of the learning algorithm robustness towards environmental noise during data acquisition, such as evaporation and contamination of odor samples.…”
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