Showing 1 - 18 results of 18 for search '(( genetic algorithm its processing ) OR ( genetic algorithm ((a processing) OR (_ processing)) ))~', query time: 0.13s Refine Results
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    Multi-Objective Optimisation of Injection Moulding Process for Dashboard Using Genetic Algorithm and Type-2 Fuzzy Neural Network by Mohammad Reza Chalak Qazani (13893261)

    Published 2024
    “…Additionally, the multi-objective genetic algorithm (MOGA) was utilised to extract the most optimal parameters for the injection moulding process, aiming to minimise shear and residual stress and thereby increase the resistance of the final product. …”
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    An Uncertainty Based Genetic Algorithm Approach for Project Resource Scheduling by ALKETBI, SAIF

    Published 2016
    “…The work presented in thesis add to the existing literature in a proposing the use of a genetic algorithm uncertain approach to resource- scheduling in projects. …”
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    A flexible genetic algorithm-fuzzy regression approach for forecasting: The case of bitumen consumption by Azadeh, Ali

    Published 2019
    “…This study aims to introduce a flexible genetic algorithm-fuzzy regression approach for forecasting the future bitumen consumption. …”
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    Multi-Modal Emotion Aware System Based on Fusion of Speech and Brain Information by M. Ghoniem, Rania

    Published 2019
    “…For classifying unimodal data of either speech or EEG, a hybrid fuzzy c-means-genetic algorithm-neural network model is proposed, where its fitness function finds the optimal fuzzy cluster number reducing the classification error. …”
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    A genetic-based fuzzy logic power system stabilizer formultimachine power systems by Abido, M.A.

    Published 1997
    “…This paper presents a novel approach to combine genetic algorithms (GA) with fuzzy logic systems to design a genetic-based fuzzy logic power system stabilizer (GFLPSS) for multimachine power systems. …”
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    Tensile Test Optimization Using the Design of Experiment and Soft Computing by Mehdi Moayyedian (14880358)

    Published 2023
    “…This study employs a hybrid soft computing approach, integrating an adaptive network-based fuzzy inference system (ANFIS), genetic algorithm (GA) optimization, and design of experiments (DOE). …”
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    Island flower pollination algorithm for global optimization by Al-Betar, Mohammed Azmi

    Published 2019
    “…Like other evolutionary algorithms, FPA has a chronic shortcoming that lies in its inability to maturely converge. …”
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    Tuning of a fuzzy logic power system stabilizer using geneticalgorithms by Abido, M.A.

    Published 1997
    “…Incorporation of GA in FLPSSs design will add an intelligent dimension to these stabilizers and significantly reduce the time consumed in the design process. It is shown that the performance of FLPSS can be improved significantly by incorporating a genetic based learning mechanism. …”
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    Parametric Design Optimization in Sustainable Urban Design: In Hot Climate by Musleh, Mousa A. M.

    Published 2012
    “…This research employs Genetic algorithms as the computational design methodology to achieve parametric design optimization to design for a more sustainable cities and urban. …”
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    Pre-production movie rating prediction using machine learning. (c2017) by Gerges, Firas Abdallah

    Published 2017
    “…In this work, we present several machine learning techniques (Support Vectors Machine, K-Nearest Neighbors, C5, Neural Networks and Case-Based Reasoning) along with a genetic algorithm to predict the success of a movie before its production using the IMDB rating as an indicator of the success. …”
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    masterThesis
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    Dynamic single node failure recovery in distributed storage systems by Itani, M.

    Published 2017
    “…With the emergence of many erasure coding techniques that help provide reliability in practical distributed storage systems, we use fractional repetition coding on the given data and optimize the allocation of data blocks on system nodes in a way that minimizes the system repair cost. We selected fractional repetition coding due to its simple repair mechanism that minimizes the repair and disk access bandwidths together with the property of un-coded repair process. …”
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