Search Results - (( location selection search algorithm ) OR ( based classification system algorithm ))*

Recommendation System Model For Decision Making in the E-Commerce Application by Mohammed Mahmudur Rahman

Automatic detection and indication of pallet-level tagging from rfid readings using machine learning algorithms by Choong, Chun Sern

“…Identifying specific locations of items such as containers, warehouse pellets, and returnable packages in a large environment, for instance, in a warehouse, requires an extensive tracking system that could identify the location through data visualization. …”
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A systematic review on emperor penguin optimizer by Abdul Kader, Md., Kamal Z., Zamli, Ahmed, Bestoun S.

“…To-date, EPO has slowly gaining considerable momentum owing to its successful adoption in many broad range of optimization problems, that is, from medical data classification, economic load dispatch problem, engineering design problems, face recognition, multilevel thresholding for color image segmentation, high-dimensional biomedical data analysis for microarray cancer classification, automatic feature selection, event recognition and summarization, smart grid system, and traffic management system to name a few. …”
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Harmony search algorithm for curriculum-based course timetabling problem by Wahid, Juliana, Mohd Hussin, Naimah

“…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 by Wahid, Juliana, Mohd Hussin, Naimah

“…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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Using artificial intelligence search in solving the camera placement problem by Altahir, A.A., Asirvadam, V.S., Hamid, N.H.B., Sebastian, P.

“…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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An enhancement of classification technique based on rough set theory for intrusion detection system application by Noor Suhana, Sulaiman

“…Henceforth, to achieve the aim, current research work proposed an enhancement of discretization algorithm based on Binning Discretization in RST to improve classification performance and to enhance the strategy of generation rules in RST to improve classification performance. …”
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Edge Detection Algorithm For Image Processing Of Search And Rescue Robot by A/L Sivem, Prasanthran

“…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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Feature extraction and selection algorithm based on self adaptive ant colony system for sky image classification by Petwan, Montha

“…The performance of FESSIC was evaluated against ten benchmark image classification algorithms and six classifiers on four ground-based sky image datasets. …”
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Dengue classification system using clonal selection algorithm / Karimah Mohd by Mohd, Karimah

“…This project focused on three main objectives: to investigate dengue data and Clonal Selection Algorithm for classification of Dengue, to design and develops Clonal Selection Classification System (CSCS) and to evaluate Clonal Selection Classification System symptoms. …”
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Overview of metaheuristic: classification of population and trajectory by Zainul Rashid, Zarina

“…Some algorithms can be defined if the developer of the system has problem specific knowledge to the solution. …”
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Performance Enhancement Of Artificial Bee Colony Optimization Algorithm by Abro, Abdul Ghani

“…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 by Farooq, H., Zakaria, M.N., Hassan, M.F., Sulaiman, Suziah

“…This paper applied an Interactive Genetic Algorithm (IGA) technique to design an visualization environment for search space. …”
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DATA CLASSIFICATION SYSTEM WITH FUZZY NEURAL BASED APPROACH by LUONG, TRUNG TUAN

“…The project's objective is identifying the available data mining algorithms in data classification and applying new data mining algorithm to perform classification tasks. …”
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Linear-PSO with binary search algorithm for DNA Motif Discovery / Hazaruddin Harun by Harun, Hazaruddin

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Lexicon-based and immune system based learning methods in Twitter sentiment analysis by Jantan, Hamidah, Drahman, Fatimatul Zahrah, Alhadi, Nazirah, Mamat, Fatimah

“…The aim of this article attempts to study the potential of this method in text classification for sentiment analysis.This study consists of three phases; data preparation; classification model development using three selected Immune System based algorithms i.e. …”
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A modified fuzzy min-max neural network with a genetic-algorithm-based rule extractor for pattern classification by Quteishat, A., Lim, C.P., Tan, K.S.

“…In this paper, a two-stage pattern classification and rule extraction system is proposed. …”
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Automatic email classification system / Phang Siew Ting by Phang , Siew Ting

“…Automatic Email Classification System is an email reader tool that implements machine learning algorithm in email classification, manipulated by a Graphical User Interface. …”
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Accuracy and performance analysis for classification algorithms based on biomedical datasets by Al-Hameli, Bassam Abdo, Alsewari, Abdulrahman A., Khubrani, Mousa, Fakhreldin, Mohammoud

“…Lazy based k-nearest neighbors (IBK) algorithm, and Rules-based OneR algorithm. …”
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Realization Of The 1D Local Binary Pattern (LBP) Algorithm In Raspberry Pi For Iris Classification Using K-NN Classifier by Siow, Shien Loong

“…Due to the current methods in feature extraction are still improving, this project proposed a new feature extraction method to increase the performance of iris classification. In this project, a classification system is proposed with the one-dimensional local binary pattern algorithm (1D-LBP) with the K-Nearest Neighbour (K-NN) classifier and the system is developed by using a Raspberry Pi 3.There are eight different subjects used to classify in this classification system and each subject consists of seven samples of normalized iris image as input to the system. …”
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