Search Results - (( data optimization method algorithm ) OR ( problem representation based algorithm ))
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1
Graph-Based Algorithm With Self-Weighted And Adaptive Neighbours Learning For Multi-View Clustering
Published 2024“…Particularly, swmcan addresses multi-view data noise using the l1-norm and optimizes the objective function through a novel iterative reweighted method. …”
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2
Optimization of RFID network planning using MDB-FA method
Published 2017“…The generated data are utilized as an input representation to apply into firefly algorithm based on Density-Based Algorithm (DBSCAN) to find the optimal network solution. …”
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3
An Improved Grasshopper Optimization Algorithm Based Echo State Network for Predicting Faults in Airplane Engines
Published 2020“…Metaheuristic algorithms are known to be excellent tools for solving optimization problems. …”
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4
An enhanced sequential exception technique for semantic-based text anomaly detection
Published 2019“…Text anomaly detection identifies deviating information from general information contained in documents. Text data are characterized by having problems related to ambiguity, high dimensionality, sparsity and text representation. …”
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5
A Method for Mapping XML DTD to Relational Schemas In The Presence Of Functional Dependencies
Published 2008“…To approach the mapping problem, three different components are explored: the mapping algorithm, functional dependency for XML, and implication process. …”
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6
Web service applications and consumer environments based on ICT-driven optimization
Published 2022“…In the field of web service application and consumer environment optimization, it has been shown that the introduction of network embedding methods can effectively alleviate the problems such as data sparsity in the recommendation process. …”
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7
Edge assisted crime prediction and evaluation framework for machine learning algorithms
Published 2022“…To anticipate occurrences, ML methods such as Decision Trees, Neural Networks, K-Nearest Neighbors, and Impact Learning are being utilized, and their performance is compared based on the data processing and modification used. …”
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8
Design of DNA fragment assembly using IWP method on application-specific integrated-circuit / Hasniliati Hassan
Published 2017“…The method proposed is to design DNA assembly algorithms in Verilog HDL and implemented it in ASIC design flow. …”
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9
k-nearest neighbour using ensemble clustering based on feature selection approach to learning relational data
Published 2016“…Due to the growing amount of data generated and stored in relational databases, relational learning has attracted the interest of researchers in recent years.Many approaches have been developed in order to learn relational data.One of the approaches used to learn relational data is Dynamic Aggregation of Relational Attributes (DARA).The DARA algorithm is designed to summarize relational data with one-to-many relations. …”
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10
Deep plant: A deep learning approach for plant classification / Lee Sue Han
Published 2018“…Hitherto, the majority of computer vision approaches have been focused on designing sophisticated algorithms to achieve a robust feature representation for plant data. …”
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11
Determining malaria risk factors in Abuja, Nigeria using various statistical approaches
Published 2018“…Therefore, this was not incorporated in BBN models. Based on cross-validation analysis, the score-based algorithm outperformed the constraint-based algorithms in the structural learning. …”
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12
A comparative representation approach to modern heuristic search methods in a job shop
Published 2008“…This research article addresses the problem of static job shop scheduling on the job-based representation and the rule-based representations. …”
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13
A review of crossover methods and problem representation of genetic algorithm in recent engineering applications
Published 2020“…This paper reviews crossover methods and problem representation, e.g. in the form of binary coded and real coded representation, used by researchers in order to solve engineering operations. …”
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14
On-orbit spatial image characterisation and restoration based on stochastic characteristic targets / Wong Soo Mee
Published 2021“…Moreover, its calibration results can be applied to an image restoration problem, to improve the spatial quality of the EOS data. …”
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15
Object-Oriented Programming semantics representation utilizing agents
Published 2011“…The algorithm requires source codes comparison based on keyword similarity to extract the words that exist in the two related source codes. …”
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16
Ball surface representations using partial differential equations
Published 2015“…This algorithm is then tested in positivity preserving of surface and image enlargement problems. …”
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17
USING LATENT SEMANTIC INDEXING FOR DOCUMENT CLUSTERING
Published 2010“…Based on the new representation, the documents are then subjected to the clustering algorithm itself, which is Fuzzy c-Means algorithm. …”
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18
Hybrid multiobjective genetic algorithm for integrated dynamic scheduling and routing of jobs and automated guided vehicles in flexible manufacturing systems
Published 2014“…The algorithm used weight mapping crossover (WMX) and Insertion Mutation (IM) as genetic operators for sub-chromosomes represented with priority-based representation. …”
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19
Optimization Of Two-Dimensional Dual Beam Scanning System Using Genetic Algorithms
Published 2008“…In addition, the performance of the new operators called GA_INSP (GA Inspection Module), DTC (Dynamic Tuning Crossover), and BCS (Bi-Cycle Selection Method) for a better evolutionary approach to the time-based problem has been discussed in the thesis. The simulation results indicate that the algorithm is able to segregate and assign the tasks for each scanning head and also able to find the shortest scanning path for different types of objects coordination. …”
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20
Food image representation based on modified orientation map
Published 2017“…Orientation map is an image representation method representing edges of objects in an image as a set of short line segments instead of pixels representation.The orientation map approach not only aims to extract the key orientation information which constitutes the semantic framework of the visual scene, but also to remove the insignificant elements which barely play a role in image understanding.However, there are two main problems in the current computational approach of orientation map: 1-the outliers in the orientation map 2- the deformities in some line segments.These two problems have an adverse impact on any algorithmic work for image interpretation. …”
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