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1
Recommendation System Model For Decision Making in the E-Commerce Application
Published 2024thesis::doctoral thesis -
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Automatic detection and indication of pallet-level tagging from rfid readings using machine learning algorithms
Published 2020“…In order to further validate the position of the tagging in the pallet box of the Random Forest model developed, a different predefined location was used to validate the model. …”
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3
Optimized techniques for landslide detection and characteristics using LiDAR data
Published 2018“…The segmentation process was optimized using Fuzzy-based Segmentation Parameter. Also, six techniques: Ant Colony Optimization (ACO), Gain Ratio (GR), Particle Swarm Optimization (PSO) and Genetic Algorithm (GA), Random forest (RF), and Correlation-based Feature Selection (CFS) were used for the feature selection. …”
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4
An adaptive ant colony optimization algorithm for rule-based classification
Published 2020“…Differing from other complex and difficult classification models, rules-based classification algorithms produce models which are understandable for users. …”
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5
Harmony search algorithm for curriculum-based course timetabling problem
Published 2013“…In this paper, harmony search algorithm is applied to curriculum-based course timetabling.The implementation, specifically the process of improvisation consists of memory consideration, random consideration and pitch adjustment.In memory consideration, the value of the course number for new solution was selected from all other course number located in the same column of the Harmony Memory.This research used the highest occurrence of the course number to be scheduled in a new harmony.The remaining courses that have not been scheduled by memory consideration will go through random consideration, i.e. will select any feasible location available to be scheduled in the new harmony solution. …”
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Harmony search algorithm for curriculum-based course timetabling problem
Published 2013“…In this paper, harmony search algorithm is applied to curriculum-based course timetabling.The implementation, specifically the process of improvisation consists of memory consideration, random consideration and pitch adjustment.In memory consideration, the value of the course number for new solution was selected from all other course number located in the same column of the Harmony Memory.This research used the highest occurrence of the course number to be scheduled in a new harmony.The remaining courses that have not been scheduled by memory consideration will go through random consideration, i.e. will select any feasible location available to be scheduled in the new harmony solution.Each course scheduled out of memory consideration is examined as to whether it should be pitch adjusted with probability of eight procedures. …”
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7
Using artificial intelligence search in solving the camera placement problem
Published 2022“…The chapter also carries out an analytical review of three main searching algorithms namely, generate and test, uninformed search, and hill climbing search algorithms. …”
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8
Knowledge base processing method based on text classification algorithm
Published 2023“…The text classification algorithm's knowledge base processing method utilizes existing data from the knowledge base to guide the construction and training of the classification model. …”
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9
A novel hybrid classification model of genetic algorithms, modified k-Nearest Neighbor and developed backpropagation neural network
Published 2014“…The performance of the proposed model was compared with thirteen well-known classification models based on seven datasets. …”
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Daisy species classification based on image using Convolutional Neural Network algorithm / Haris Hidayatullah Khaimuza
Published 2024“…Second objective is to develop the prototype of daisy species classification based on image using CNN algorithm. The last objective is to evaluate the accuracy of CNN model in the daisy species classification based on image. …”
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12
Edge Detection Algorithm For Image Processing Of Search And Rescue Robot
Published 2016“…This project entitled “ Edge Detection Algorithm for Image Processing of Search and Rescue Robot ” has its primary purpose to identify an optimum edge detection algorithm for image processing of search and rescue robot. …”
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Final Year Project -
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Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model
Published 2018“…Hence, this situation is believed in yielding of decreasing the classification accuracy. In this article, we present the exploration on the combination of the clustering based algorithm with an ensemble classification learning. …”
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An efficient intrusion detection model based on hybridization of artificial bee colony and dragonfly algorithms for training multilayer perceptrons
Published 2020“…This study proposes a new binary classification model for intrusion detection, based on hybridization of Artificial Bee Colony algorithm (ABC) and Dragonfly algorithm (DA) for training an artificial neural network (ANN) in order to increase the classification accuracy rate for malicious and non-malicious traffic in networks. …”
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Performance Enhancement Of Artificial Bee Colony Optimization Algorithm
Published 2013“…To overcome the problems, this research work has proposed few modified and new ABC variants; Gbest Influenced-Random ABC (GRABC) algorithm systematically exploits two different mutation equations for appropriate exploration and exploitation of search-space, Multiple Gbest-guided ABC (MBABC) algorithm enhances the capability of locating global optimum by exploiting so-far-found multiple best regions of a search-space, Enhanced ABC (EABC) algorithm speeds up exploration for optimal-solutions based on the best so-far-found region of a search-space and Enhanced Probability-Selection ABC (EPS-ABC) algorithm, a modified version of the Probability-Selection ABC algorithm, simultaneously capitalizes on three different mutation equations for determining the global-optimum. …”
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A Multidimensional Search Space Using Interactive Genetic Algorithm
Published 2010“…This paper applied an Interactive Genetic Algorithm (IGA) technique to design an visualization environment for search space. …”
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Selection and optimization of peak features for event-related eeg signals classification / Asrul bin Adam
Published 2017“…At first, a peak classification algorithm is developed based on the general following processes including peak candidate identification, feature extraction, and classification. …”
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Ideal combination feature selection model for classification problem based on bio-inspired approach
Published 2020“…The next step is to define an optimized feature set for classification task. Performance metrics are analyzed based on classification accuracy and the number of selected features. …”
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