Search Results - (( java application model algorithm ) OR ( parameter navigation learning algorithm ))

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    Chiller energy prediction in commercial building : A metaheuristic-enhanced deep learning approach by Mohd Herwan, Sulaiman, Zuriani, Mustaffa

    Published 2024
    “…TLBO's adept navigation of the intricate parameter space of DL yields highly precise predictions for chiller energy consumption. …”
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    Real-time algorithmic music composition application. by Yap, Alisa Yi Hui

    Published 2022
    “…This project is about the study of evolutionary music, and focuses on the development of an algorithmic music composer using the Java programming language. …”
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    Final Year Project / Dissertation / Thesis
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    A framework of modified adaptive neuro-fuzzy inference engine by Hossen, Md. Jakir

    Published 2012
    “…The Takagi-Sugeno-Kang (TSK) type fuzzy inference system was chosen and constructed by an automatic generation of clusters as well as membership functions and minimal rules through the use of hybrid fuzzy clustering and the modified apriori algorithms respectively. The developed TSK type fuzzy inference engine is called modified adaptive fuzzy inference engine (MAFIE) and its parameters were then adjusted by the hybrid learning algorithm using adaptive neural network architecture towards improved performance which is called MANFIE. …”
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    Thesis
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    A Toolkit for Simulation of Desktop Grid Environment by FOROUSHAN, PAYAM CHINI

    Published 2014
    “…In this type of environment it is nearly impossible to prove the effectiveness of a scheduling algorithm. Hence the main objective of this study is to develop a desktop grid simulator toolkit for measuring and modeling scheduler algorithm performance. …”
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    Final Year Project
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    Secure Image Steganography Using Encryption Algorithm by Siti Dhalila, Mohd Satar, Roslinda, Muda, Fatimah, Ghazali, Mustafa, Mamat, Nazirah, Abd Hamid, An, P.K

    Published 2016
    “…The objective of this study is to enhance the confidentiality and security of the image steganography application by combining cryptography algorithm. In this proposed model, the RSA algorithm is used to encrypt a secret message into an unreadable ciphertext before hiding it in the image. …”
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    Conference or Workshop Item
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    A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment by Ruzita, Ahmad

    Published 2013
    “…This thesis describes original research in the field of software quality model by presenting a Feature Ranking Algorithm (FRA) for Pragmatic Quality Factor (PQF) model. …”
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    Thesis
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    Network game (Literati) / Chung Mei Kuen by Chung, Mei Kuen

    Published 2003
    “…Therefore, efficient and robust servers that process separate client connections in separate threads are needed. Java applet is a well-known and widely used example of mobile code (a variation on the traditional client-server model). …”
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    Thesis
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    Rethinking environmental sound classification using convolutional neural networks: optimized parameter tuning of single feature extraction by Al-Hattab, Yousef Abd, Mohd Zaki, Hasan Firdaus, Shafie, Amir Akramin

    Published 2021
    “…We demonstrate that such a simple network can considerably outperform several conventional and deep learning-based algorithms. Through a carefully and empirically parameters fine-tuning of the data input, we reported a model that is significantly less complex in the architecture yet has recorded a similar accuracy of 95.59% compared to state-of-the-art deep models on UrbanSound8k dataset. …”
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    Factor Strategy Model: Proofs of Prototype Concept for Software Quality Evaluation by Nathan, Darmawan, Ooi, Keng Boon, Chong, Alain Yee Loong, Tan, Boon In

    Published 2010
    “…Thus, by providing an algorithm analyzer to analyze the quality of design of the software product, developers or students can identify possible bad software design in their application.…”
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    Development of predictive modeling and deep learning classification of taxi trip tolls by Al-Shoukry, Suhad, M. Jawad, Bushra Jaber, Zalili, Musa, Sabry, Ahmad H.

    Published 2022
    “…Once the data has been prepared, it’s time to begin the supervised machine learning process and test a number of ways to identify the best model, such as the type of model that should be used, the important features, and the best parameters of the model to find the best fit for the considered data. …”
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    Article