Search Results - (( developing spatial optimization algorithm ) OR ( java data prediction algorithm ))
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Mapreduce algorithm for weather dataset
Published 2017“…In addition, these characteristics also contribute to the complexity on the data processing and prediction. Big Data analytics is a new concept to process the Big Data. …”
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Thesis -
2
Modeling forest fires risk using spatial decision tree
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Conference or Workshop Item -
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MapReduce algorithm for weather dataset
Published 2018“…In addition, these characteristics also contribute to the complexity on the data processing and prediction. Big Data analytics is a new concept to process the Big Data. …”
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Research Report -
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Genetic-local hybrid optimizer for solving advance layout problem
Published 2006“…The research studies the problem of adding the heterogeneous objects, continuous placement in the general spatial layout problem. Results are achieved through the use of local optimizer, separation algorithm with genetic algorithm also called hybrid simple genetic. …”
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Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly
Published 2019“…This prediction can be made by cluster the new data with the old data and observe where the data belongs. …”
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Thesis -
7
A spatial decision support system framework for optimization of cropping pattern and water resources allocation at pasargard plains, fars province, Iran
Published 2014“…In the present study, a Spatial Decision Support System (SDSS) framework was developed to tackle the above-mentioned problems and was used to propose optimal decisions for agricultural lands of the Pasargad plain in central Iran as a case study. …”
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8
A Framework for Green Energy Resources Identification and Integration Supported by Real-Time Monitoring, Control, and Automation Applications
Published 2025“…The second layer employed spatial data and the fuzzy Technique for Order Preference by Similarity to Ideal Solution algorithm to refine potential solar energy sites, yielding the top 100 optimal locations. …”
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9
Common spatial pattern with feature scaling (FSc-CSP) for motor imagery classification
Published 2017“…Previously, to extract useful information, various filters are introduced, such as spatial, temporal, and spectral filtering. A spatial filtering algorithm called Common Spatial Pattern (CSP) was developed and known to have excellent performance, especially in motor imagery for BCI application. …”
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AI powered asthma prediction towards treatment formulation: an android app approach
Published 2022“…Besides, an android application is being cre-ated to give therapy based on machine learning predictions. To collect data, we enlisted the help of 4,500 people. …”
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Resource allocation in coordinated multipoint long term evolution-advanced networks
Published 2015“…The resource allocation algorithm is developed through three phases, namely Low-Complexity Resource Allocation (LRA), Optimized Resource Allocation (ORA) and Cross-Layer Design of ORA (CLD-ORA). …”
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12
Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…Thus, there is a need to automate the process of identifying and predicting (positive, negative, or neutral class) these cyber-trooping data. …”
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Thesis -
13
AI powered asthma prediction towards treatment formulation : An android app approach
Published 2022“…Besides, an android application is being cre-ated to give therapy based on machine learning predictions. To collect data, we enlisted the help of 4,500 people. …”
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14
CROWDSOURCING-BASED MOBILE APPLICATION FOR SUPERMARKET STOCK AVAILABILITY CHECKER
Published 2020“…This project is implementing spatial crowdsourcing technology in hope to optimize the frequent updates of the stock availability by means of contributions from users. …”
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Final Year Project -
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An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…In the second phase, a classifier ensemble learning model is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on Binary Quantum Gravitational Search Algorithm (QBGSA), (ii) To mine data streams using various data chunks and overcome a failure of single classifiers based on SVM, MLP and K-NN algorithms. …”
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Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning
Published 2016“…Moreover, instead of concatenating feature vectors together and send to classifier, sparse coding and dictionary learning methods are used and instead of considering all features as one view (visual feature), K-SVD algorithm that is one of the famous algorithms for sparse representation is optimized and developed to multi-view model.The experimental results prove that the proposed methods has improved accuracy by 53.77% compared to concatenating features and classic K-SVD dictionary learning model as well.…”
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17
Modelling of optimized hybrid debris flow using airborne laser scanning data in Malaysia
Published 2019“…The general objective of the study was the development of optimized hybrid debris flow models using airborne laser scanning data and Machine learning algorithms in Malaysia. …”
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Pattern classification of human interactions from videos / Muhsin Abdul Mohammed
Published 2018“…There have been investigations made to identify the best spatial and temporal architectures that would give the optimal result.…”
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. The proposed model will be tested and evaluated on both NSL-KDD and KDD-CUP 99 using several performance metrics.…”
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Efficient and low complexity modulation classification algorithm for MIMO systems
Published 2015“…This study develops a feature-based Automatic Modulation Classification (AMC) algorithm for spatially multiplexed Multiple-Input Multiple-Output (MIMO) systems employing two Higher Order Cumulants (HOCs) of the estimated transmit signal streams as discriminating features and a multiclass Support Vector Machine (SVM) as a classification system. …”
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