Search Results - (( mobile evaluation search algorithm ) OR ( data classification using algorithm ))*
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The classification of wink-based eeg signals by means of transfer learning models
Published 2021“…The implementation of pre-processing algorithms has been demonstrated to be able to mitigate the signal noises that arises from the winking signals without the need for the use signal filtering algorithms. …”
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A coverage path planning approach for autonomous radiation mapping with a mobile robot
Published 2023Article -
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Effectiveness of mobile agent for query retrieval
Published 2002“…The Mobile Agent Search System (MaSS) has been developed to reduce the time for searching and retrieving information from the Internet. …”
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MOBILE DICTIONARY
Published 2005“…The output of this system will be evaluated by users who already have experienced in using existing electronic dictionaries based on MobileDic accuracy as well as its usefulness. …”
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Final Year Project -
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Context-Aware Recommender System based on machine learning in tourist mobile application / Nor Liza Saad … [et al.]
Published 2022“…This paper provides the fundamental knowledges on machine learning design and evaluation useful in the tourist mobile application with context-aware recommender system.…”
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A comprehensive overview of classical and modern route planning algorithms for self-driving mobile robots
Published 2022“…Mobile robots are increasingly being applied in a variety of sectors, including agricultural, firefighting, and search and rescue operations. …”
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Embedded parallel distributed artificial intelligent processors for adaptive beam forming in WCDMA system
Published 2023Subjects:Conference paper -
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Is gravitational search algorithm's initial gravitational constant a function dependent parameter?
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Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms
Published 2005“…In cluster generating process, the developed BBSI algorithm was used to select the best band combination for generating cluster by using Iterative self- Organizing Data Analysis (ISODATA) technique. …”
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Case Slicing Technique for Feature Selection
Published 2004“…Since the 1960s, many algorithms for data classification have been proposed. …”
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A comparison study of classifier algorithms for mobile-phone’s accelerometer based activity recognition
Published 2012“…As a continuation of the research towards the search for a suitable and reliable algorithm for real-time activity recognition using mobile phone, an evaluation and comparison study of the performance of seven different categories of classifier algorithms in classifying user activities were conducted. …”
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Dengue classification system using clonal selection algorithm / Karimah Mohd
Published 2012“…Some of the dengue data are used to test the dengue classification system to produce the classification accuracy. …”
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Enhancing Classification Algorithms with Metaheuristic Technique
Published 2024“…Implementing this process uses classification algorithms such asNaïve Bayes, Support Vector Machine,and Random Forest. …”
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Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd
Published 2022“…Classification is a data mining technique used to classify varied data types according to a specific criterion. …”
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Attribute related methods for improvement of ID3 Algorithm in classification of data: A review
Published 2020“…Nevertheless, there are some limitations in ID3 algorithm that can affect the performance in the classification of data. …”
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Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition
Published 2017“…Phase 1 is mainly to evaluate the performance of clustering algorithm (K-Means and FCM). Phase 2 is to study the performance of proposed integration system which using the data clustered to be used as train data for Naïve Bayes classifier. …”
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Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model
Published 2018“…Expectation maximization (EM) is one of the representatives clustering algorithms which have broadly applied in solving classification problems by improving the density of data using the probability density function. …”
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