Search Results - (( processes specification based algorithm ) OR ( data classification problems algorithm ))
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1
Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd
Published 2022“…The study verified that the FID3-DBD algorithm could classify the continuous data, and the BFID3-DBD algorithm overcame the overfitting issue, reduced high variance, and increased test data classification accuracy.…”
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2
Weight Optimization in Recurrent Neural Networks with Hybrid Metaheuristic Cuckoo Search Techniques for Data Classification
Published 2015“…Specifically, some selected benchmark classification problems are used. …”
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3
Improved intrusion detection algorithm based on TLBO and GA algorithms
Published 2021“…This is attributable to the increasing number of audit data features and the decreasing performance of human-based smart Intrusion Detection Systems (IDS) regarding classification accuracy and training time. …”
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4
Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad
Published 2018“…This learning algorithm represents an automatic generation of membership functions and rules from the data. …”
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5
Deep learning object detector using a combination of Convolutional Neural Network (CNN) architecture (MiniVGGNet) and classic object detection algorithm
Published 2020“…MiniVGGNet is an architecture network used to train an object classification, and the data used for this purpose was collected from specific indoor environment building. …”
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6
The effect of data preprocessing on the performance of artificial neural networks techniques for classification problems
Published 2012“…Improving training efficiency of ANN based algorithm is an active area of research and numerous papers have been reviewed in the literature. …”
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7
An ensemble of neural network and modified grey wolf optimizer for stock prediction
Published 2019“…The proposed approachoutperforms existing available meta-heuristic algorithms. Specifically, the proposed model achieved 97% classification rate, 95% precise prediction and less than 2.0 error rate. …”
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8
Prognostic Health Management of Pumps Using Artificial Intelligence in the Oil and Gas Sector: A Review
Published 2022“…While the need for selecting appropriate training algorithms is seen to be significant. Interestingly, no specific method or algorithm exists for a given problem instead the solution relies on the type of data and the algorithmâ��s or methodâ��s aptitude for resolving the provided errors. …”
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9
An enhanced gated recurrent unit with auto-encoder for solving text classification problems
Published 2020“…However, GRU suffered from three major issues when it is applied for solving the text classification problems. The first drawback is the failure in data dimensionality reduction, which leads to low quality solution for the classification problems. …”
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10
Fuzzy support vector machine based fall detection method for traumatic brain injuries: A new systematic approach of combining fuzzy logic with support vector machine to achieve hig...
Published 2022“…One of the most commonly used algorithms is Support Vector Machine (SVM). However, classical SVM can neither use prior knowledge to process accurate classifications nor solve problems characterized by ambiguity. …”
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11
Anomaly behavior detection using flexible packet filtering and support vector machine algorithms
Published 2016“…The main method is related to processing and filtering data packets using different types of packet filtering on network system and, more specifically, capturing and filtering data packets transmitted on high speed communications links for errors and attackers’ detection and signal integrity analysis. …”
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12
Automatic detection and indication of pallet-level tagging from rfid readings using machine learning algorithms
Published 2020“…The ensemble learning technique, changes of activation function in Neural Network as well as the unsupervised learning (k-means clustering algorithm and Friis Transmission Equation) was also applied to classify the multiclass classification in pallet-level. …”
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13
An automated high-accuracy detection scheme for myocardial ischemia based on multi-lead long-interval ECG and Choi-Williams time-frequency analysis incorporating a multi-class SVM...
Published 2021“…The classification process uses the data of 92 normal and 266 patients from four different databases. …”
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14
Q-Learning-based detection of IPv6 intrusions: a behavioral and performance study
Published 2025“…To address this limitation, the present study proposes a self-learning model using reinforcement learning techniques, specifically the Q-Learning algorithm, to classify network intrusions based on learned behavioural patterns autonomously. …”
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15
Context enrichment framework for sentiment analysis in handling word ambiguity resolution
Published 2024“…However, ambiguous words pose a challenge for sentiment analysis algorithms as they require the identification of the correct meaning and word polarity within a specific context. …”
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16
Dengue classification system using clonal selection algorithm / Karimah Mohd
Published 2012“…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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17
Wood species recognition based on phase - only correlation (POC) technique
Published 2013“…By applying all three steps, the test image is found to either match or not match the training data. Next, the classification process is performed with the help of the K-Neighbour Network (KNN) technique; where it helps to classify the wood images. …”
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18
An improve unsupervised discretization using optimization algorithms for classification problems
Published 2024“…This paper addresses the classification problem in machine learning focusing on predicting class labels for datasets with continuous features. …”
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An improve unsupervised discretization using optimization algorithms for classification problems
Published 2024“…This paper addresses the classification problem in machine learning, focusing on predicting class labels for datasets with continuous features. …”
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A derivative-free optimization method for solving classification problem
Published 2010“…Problem statement: The aim of data classification is to establish rules for the classification of some observations assuming that we have a database, which includes of at least two classes. …”
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