Search Results - (( leaf optimization based algorithm ) OR ( variable estimation learning algorithm ))

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  1. 1

    Automated plant classification system using a hybrid of shape and color features of the leaf by Hamid, Laith Emad

    Published 2016
    “…Automated plant leaf classification is a computerized approach that employs computer vision and machine learning algorithms to identify a plant based on the features of its leaf. …”
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    Thesis
  2. 2

    Assessment of forest aboveground biomass estimation from superview-1 satellite image using machine learning approaches / Azinuddin Mohd Asri by Mohd Asri, Azinuddin

    Published 2022
    “…The suitable independent variables (hL, DBH, and CPA) were vital to estimating the dependent variable (Sc) and producing a carbon stock map for the final result. …”
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    Thesis
  3. 3

    Feature decision-making ant colony optimization system for an automated recognition of plant species by Ghasab, Mohammad Ali Jan, Khamis, Shamsul, Faruq, Mohammad, Fariman, Hessam Jahani

    Published 2015
    “…In the present paper, an expert system for automatic recognition of different plant species through their leaf images is investigated by employing the ant colony optimization (ACO) as a feature decision-making algorithm. …”
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    Article
  4. 4

    Plant leaf recognition algorithm using ant colony-based feature extraction technique by Ghasab, Mohammad Ali Jan

    Published 2013
    “…Then, based on the characteristics of each species, decision making is done by means of ant colony optimisation as a search algorithm to return the optimal subset of features regarding the related species. …”
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    Thesis
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    SLIDING WINDOW TRAINING ALGORITHMS USING MLP-NETWORK FOR CORRELATED AND LOST PACKET DATA by AHMED IZZELDIN, HUZAIFA TAWFEIG

    Published 2012
    “…This thesis gives a systematic investigation of various MLP learning mainly Sliding Window (SW) learning mode which is treated as the adaptation of offline algorithms into online application Consequently this thesis reviews various offline algorithms including: batch backpropagation, nonlinear conjugate gradient, limited memory and full-memory Broyden, Fletcher, Goldfarb and Shanno algorithms and different forms of the latest proposed bimary ensemble learning. …”
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    Thesis
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    Dynamic Bayesian Networks and Variable Length Genetic Algorithm for Dialogue Act Recognition by Ali Yahya, Anwar

    Published 2007
    “…In the selection phase, a new variable length genetic algorithm is applied to select the lexical cues. …”
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    Thesis
  9. 9

    Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning by Safa, Soodabeh

    Published 2016
    “…Second one is gist from global features of leaf images. gist descriptor is based on spatial layout of colors, orientation and principal texture. …”
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    Thesis
  10. 10

    Robust Data Fusion Techniques Integrated Machine Learning Models For Estimating Reference Evapotranspiration by Chia, Min Yan

    Published 2022
    “…Observations of the results of this study revealed that the solar radiation (Rs) is the most essential variable for estimating ET0 in Peninsular Malaysia. …”
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    Final Year Project / Dissertation / Thesis
  11. 11

    A case study on quality of sleep and health using Bayesian networks by Hong , Choon Ong, Chiew , Seng Lee, Chye , Ching Sia

    Published 2012
    “…The network scores computation is implemented to estimate the fitting of the resulting network of each structural learning algorithm in order to choose the best-fitted network. …”
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    Article
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    Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

    Published 2018
    “…In the developed feature selection approach, multi-objective binary-valued backtracking search algorithm (MOBBSA) is used as an efficient evolutionary search algorithm to search within different combinations of input variables and selects the non-dominated feature subsets, which minimize simultaneously both the estimation error and the number of features. …”
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    Thesis
  14. 14

    Enhanced Adaptive Confidence-Based Q Routing Algorithms For Network Traffic by Yap, Soon Teck

    Published 2004
    “…The ECDRQ Routing Algorithm integrates the ECQ and Dual Reinforcement Q (DRQ) Routing Algorithms with Alternative Q Value Approach to minimise the effect of partially learning cycle. …”
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    Thesis
  15. 15

    Deep plant: A deep learning approach for plant classification / Lee Sue Han by Lee , Sue Han

    Published 2018
    “…They look for the procedures or algorithms that maximize the use of leaf databases for plant predictive modelling, but this results in leaf features which are liable to change with different leaf data and feature extraction techniques. …”
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    Thesis
  16. 16

    Applying machine learning and particle swarm optimization for predictive modeling and cost optimization in construction project management by almahameed, Bader aldeen, Bisharah, Majdi

    Published 2024
    “…Particle Swarm Optimization (PSO) has demonstrated its efficacy in addressing the issue of construction waste reduction and enhancing the accuracy of cost estimation through the identification of optimal combinations of variables. …”
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    Article
  17. 17

    Creating Air Temperature Models for High-Elevation Desert Areas Using Machine Learning by Forooshani, Massoud, Gegov, Alexander, Pepin, Nick, Adda, Mo

    Published 2023
    “…This is particularly important in high-elevation regions. In this study, we estimate Ta in the high-elevation desert zone of Kilimanjaro (>4500m) using four models (five models including the benchmark model) with unique sets of inputs using five machine learning (ML) algorithms. …”
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    A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing by Wei , Yaxing

    Published 2024
    “…Finally, one key drawback of estimating streamflow outlined above is that it does not account for variability. …”
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    Thesis