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Combinatorial Clustering Algorithm of Quantum-Behaved Particle Swarm Optimization and Cloud Model

Mi-Yuan Shan, Ren-Long Zhang, Li-Hong Zhang
2013 Mathematical Problems in Engineering  
The algorithm employs a novel probability model as well as a permutation-based local search method. We are setting the parameters of COCQPSO based on the design of experiment.  ...  We propose a combinatorial clustering algorithm of cloud model and quantum-behaved particle swarm optimization (COCQPSO) to solve the stochastic problem.  ...  A novel optimization algorithm, based on a modified binary-PSO with mutation (MBPSOM) combined with a support vectormachine (SVM), was proposed to select the fault feature variables for fault diagnosis  ... 
doi:10.1155/2013/406047 fatcat:3zmj3xxzvnf6lnyvatmfrvibjy

P System–Based Clustering Methods Using NoSQL Databases

Péter Lehotay-Kéry, Tamás Tarczali, Attila Kiss
2021 Computation  
For this purpose, we discover the possibilities of a clustering algorithm based on P systems when used alongside NoSQL database systems, that are designed to manage big data.  ...  , so that, based on this, a more substantiated decision can be made, meaning which database management system should be connected to the system.  ...  Based on [37] the developers of MongoDB aimed to create a database that worked with documents, usually with JSON in this case, and that was fast, scalable, and easy to use.  ... 
doi:10.3390/computation9100102 fatcat:lo5zbb3xojdxzocoxvgoozuxyi

Novel Two-Dimensional Visualization Approaches for Multivariate Centroids of Clustering Algorithms

Yunus Doğan, Feriştah Dalkılıç, Derya Birant, Recep Alp Kut, Reyat Yılmaz
2018 Scientific Programming  
In this study, five novel hybrid approaches were proposed to eliminate these drawbacks by using the quantum genetic algorithm (QGA) method and four feature selection methods, Pearson's correlation, gain  ...  The dimensionality reduction and visualization problems associated with multivariate centroids obtained by clustering algorithms are addressed in this paper.  ...  of K-means++, but none on visualizing a 2D map for the clusters of this successful algorithm. erefore, in this study, a novel approach to visualizing K-means++ clusters on a 2D map is detailed.  ... 
doi:10.1155/2018/9253295 fatcat:nezofrfgnbdehajuo5ifbgvjui

A Hybrid Black Hole Algorithm with Genetic Algorithm for Solving Data Clustering Problems

Ahmed I. Taloba , Et. al.
2021 Turkish Journal of Computer and Mathematics Education  
Issues of data clustering have recently received research attention and as such, a nature-based optimization algorithm called Black Hole (BH) has said to be suggested as an arrangement to data clustering  ...  Furthermore, it also revealed a high convergence rate which used six real datasets sourced of the UCI machine learning laboratory, indicating fine conduct of the hybrid algorithm on data clustering problems  ...  A novel hybrid algorithm was accessible based on top of the cluster center initialization algorithm (CCIA), bees' algorithm, as well as level of dissimilarity evolution by [55] (collectively acknowledged  ... 
doi:10.17762/turcomat.v12i2.1122 fatcat:753bslyv5bfhlgr4jx3wj5uz7e

Recent Advances in Information Technology

Fei Yu, Chin-Chen Chang, Yiqin Lu, Jian Shu, Yan Gao, Guangxue Yue, Zuo Chen
2014 The Scientific World Journal  
Wu et al. in their paper entitled "Mixed pattern matching-based traffic abnormal behavior recognition" propose a trajectory pattern learning method based on dynamic time warping (DTW) and spectral clustering  ...  Li et al. presents a novel method with appearance model described by double templates based on timed motion history image with HSV color histogram feature (tMHI-HSV).  ...  on Information Processing (ISIP 2013).  ... 
doi:10.1155/2014/746479 pmid:25110742 pmcid:PMC4119702 fatcat:f3yq2agpevcvdbxe44umitvxa4

Survey on lie group machine learning

Mei Lu, Fanzhang Li
2020 Big Data Mining and Analytics  
This study aims to provide a comprehensive survey on recent advances in Lie group machine learning.  ...  Lie group learning is a vibrant field of increasing importance and extraordinary potential and thus needs to be developed further.  ...  [93] proposed a 3D-based deep convolutional neural network for action recognition with a depth sequence algorithm.  ... 
doi:10.26599/bdma.2020.9020011 fatcat:ki4l7b5o6ncltfgcu462flxsiq

Utilizing Quantum Biological Techniques on a Quantum Processing Unit for Improved Protein Binding Site Determination [article]

Samarth Sandeep, Vaibhav Gupta, Torin Keenan
2020 bioRxiv   pre-print
The ability to provide this advantage comes from a new approach to biophysics, dubbed many-body biological quantum systems, that are modeled using quantum processing units and quantum algorithms.  ...  Iff Technologies has constructed a tool named Polar+ that can predict protein-to-protein binding sites on a given receptor protein that operates faster and at a higher quality than the prominent industry  ...  What is the improvement of using a quantum mechanical model for binding over other algorithms? A.  ... 
doi:10.1101/2020.03.20.000950 fatcat:kklksjct6vb2tkpygrj6lkwkji

Novel Approaches for Applying Linguistic Processing Techniques Based on Pattern Recognition and Machine Learning

2017 Journal of Information Processing Systems  
publishes a broad array of subjects related to information communication technology in a wide variety of prevalent and advanced fields, including systems, networks, architecture, algorithms, applications  ...  their related research areas by presenting new techniques, concepts, or analyses, and feature experience reports, experiments involving the implementation and application of new theories, and tutorials on  ...  Clustering is a popular technique that has been applied to many research domains, such image analysis, pattern recognition, data mining, medical science, etc. [40] .  ... 
doi:10.3745/jips.00.0006 fatcat:psfo363clrfqxku7dfg33gsaqu

A quantum-inspired multimodal sentiment analysis framework

Yazhou Zhang, Dawei Song, Peng Zhang, Panpan Wang, Jingfei Li, Xiang Li, Benyou Wang
2018 Theoretical Computer Science  
., an image that is associated with a textual description or a set of textual labels).  ...  ., A Quantum-Inspired Multimodal Sentiment Analysis Framework, Theoret. Comput. Sci. (2018), https://doi.  ...  In this paper, we propose a novel quantum-inspired framework to address the above two challenges.  ... 
doi:10.1016/j.tcs.2018.04.029 fatcat:rpnlxnvps5fklcqozncurg3tyq

TLATR: Automatic Topic Labeling using Automatic (Domain-Specific) Term Recognition

Ciprian-Octavian Truica, Elena-Simona Apostol
2021 IEEE Access  
To prove that our novel method extracts relevant topic labels, we compare TLATR with two state-of-the-art methods, one supervised and one unsupervised, provided by the NETL Automatic Topic Labelling system  ...  TLATR uses domain-specific multi-terms that appear in the set of documents belonging to a topic.  ...  Other methods based on C-Value were proposed, e.g., NC-Value that better combines linguistic patterns with the textual context [16] , [17] .  ... 
doi:10.1109/access.2021.3083000 fatcat:fguiv45azbamzorh3byvijw2ki

Survey of Promising Technologies for Quantum Drones and Networks

Adarsh Kumar, Surbhi Bhatia, Keshav Kaushik, Manjula Gandhi, Gayathri Devi, Diego Pacheco, Arwa Mashat
2021 IEEE Access  
As a result, the primary synergies between QC and AI could lead to new insights in areas as statistical inference, Bayesian networks, and pattern recognition (e.g., recognition and discrimination of quantum  ...  The algorithm consists of subpopulations, and these sub-populations are further divided into clusters, and each cluster is called a cosmos [208] .  ... 
doi:10.1109/access.2021.3109816 fatcat:gkyevfoqrfertef7j7gjzcstii

Quantum Machine Learning for Finance [article]

Marco Pistoia, Syed Farhan Ahmad, Akshay Ajagekar, Alexander Buts, Shouvanik Chakrabarti, Dylan Herman, Shaohan Hu, Andrew Jena, Pierre Minssen, Pradeep Niroula, Arthur Rattew, Yue Sun (+1 others)
2021 arXiv   pre-print
This review paper presents the state of the art of quantum algorithms for financial applications, with particular focus to those use cases that can be solved via Machine Learning.  ...  Quantum computers are expected to surpass the computational capabilities of classical computers during this decade, and achieve disruptive impact on numerous industry sectors, particularly finance.  ...  Inspired by quantum mechanics and suitable for high-dimensional data, Quantum Clustering (QC) [64] is an algorithm that belongs to the family of density-based clustering algorithms, where clusters are  ... 
arXiv:2109.04298v1 fatcat:7mrhh6b6hza73l7cn4c3uygxga

Big data in healthcare: management, analysis and future prospects

Sabyasachi Dash, Sushil Kumar Shakyawar, Mohit Sharma, Sandeep Kaushik
2019 Journal of Big Data  
Various public and private sector industries generate, store, and analyze big data with an aim to improve the services they provide.  ...  Otherwise, seeking solution by analyzing big data quickly becomes comparable to finding a needle in the haystack.  ...  , choosing treatment option for a patient based on clustering and decision trees.  ... 
doi:10.1186/s40537-019-0217-0 fatcat:6yb7kk5ervaqhjt6lhe3utkivq

Editorial: Security and Privacy in Computing and Communications

Zheli Liu, Jin Li, Ilsun You, Siu-Ming Yiu
2020 Journal on spesial topics in mobile networks and applications  
With the advances in information systems and technologies, we are witnessing the advent of novel challenges on security and privacy in computing and communications for mobile devices, cloud and Internet  ...  , and propose a revocable group signatures scheme that is more efficient and scalable compared to previous ones, especially for Sign and Verify algorithms, which are performed much more frequently than  ...  The ninth article, "PRIA: a Multi-source Recognition Method Based on Partial Observation in SIR Model" proposed a novel PRIA algorithm to locate multiple propagation sources.  ... 
doi:10.1007/s11036-020-01683-4 fatcat:lf6rubtslbex5f2g2cku4ydy7i

The Dichotomy of Neural Networks and Cryptography: War and Peace

Behrouz Zolfaghari, Takeshi Koshiba
2022 Applied System Innovation  
This side of the dichotomy can be interpreted as a war declared by neural networks. On the other hand, neural networks and cryptographic algorithms can mutually support each other.  ...  There are, to the best of our knowledge, no current surveys that take a comprehensive look at the many ways neural networks are currently interacting with cryptography.  ...  novel design combines long short-term memory recurrent networks with convolutional NNs, for pattern and signature recognition, respectively.Some researchers designed systems focusing on factors external  ... 
doi:10.3390/asi5040061 fatcat:6p5evyj7h5dvfckt6qzmqbzipi
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