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A Notable Swarm Approach to Evolve Neural Network for Classification in Data Mining [chapter]

Satchidananda Dehuri, Bijan Bihari Mishra, Sung-Bae Cho
2009 Lecture Notes in Computer Science  
This paper presents a novel and notable swarm approach to evolve an optimal set of weights and architecture of a neural network for classification in data mining.  ...  The computation time of their proposed work is quite high due to the partial training. Carvalho et al.  ...  Further, as they are using PT algorithm for training so their method introduces overhead in computational time.  ... 
doi:10.1007/978-3-642-02490-0_136 fatcat:267lhvet2rfhjd45lauz6tygzq

A Novel Evolutionary Algorithm for Hierarchical Neural Architecture Search [article]

Aristeidis Chrostoforidis, George Kyriakides, Konstantinos Margaritis
2021 arXiv   pre-print
First, we apply it to the image recognition dataset, Fashion-MNIST, where the algorithm is able to generate a network with 93.2% accuracy.  ...  While the approach still suffers from some common problems present in most evolutionary algorithms, mainly the large amounts of time required to train and evaluate candidate networks such negative effects  ...  During the first step of network generation, N neural modules are sampled from the notable modules list, utilizing their average fitness as weights.  ... 
arXiv:2107.08484v1 fatcat:l6ph4xsmozegrgyj3chdhzqi7i

A suspect-oriented intelligent and automated computer forensic analysis

M. Al Fahdi, N.L. Clarke, F. Li, S.M. Furnell
2016 Digital Investigation. The International Journal of Digital Forensics and Incident Response  
Computer forensics faces a range of challenges due to the widespread use of computing technologies.  ...  A total of 275 sets of experiments were conducted to determine the viability of clustering across a range of network configurations.  ...  Notably, as the SOM network size increases, both the identification rate of notable files and the volume of noise files decreases.  ... 
doi:10.1016/j.diin.2016.08.001 fatcat:waq3ky7l3zfhvnawjdz4pves4i

Soft computing approaches for next-generation sustainable systems (SCNGS)

Pasumpon Pandian, Xavier Fernando, Tomonobu Senjyu
2019 Soft Computing - A Fusion of Foundations, Methodologies and Applications  
Notably, researcher uses the soft computing approaches in data mining, machine learning, sustainable computing, capsule networks, neural networks and fuzzy linear systems to provide the intelligent solutions  ...  The most integration models of soft computing techniques are fuzzy logic, deep learning, evolutionary computation, optimization algorithm, metaheuristics, Bayesian networks, expert systems, perceptron,  ...  Notably, researcher uses the soft computing approaches in data mining, machine learning, sustainable computing, capsule networks, neural networks and fuzzy linear systems to provide the intelligent solutions  ... 
doi:10.1007/s00500-019-03860-4 fatcat:ihnpmw2vunhmnk3ht3wh2zlrwi

From Bitcoin to Bitcoin Cash

Marco Alberto Javarone, Craig Steven Wright
2018 Proceedings of the 1st Workshop on Cryptocurrencies and Blockchains for Distributed Systems - CryBlock'18  
Notably, we analyze their global structure and we try to evaluate if they are provided with a small-world behavior.  ...  In this work, we perform a preliminary investigation on two kinds of network, i.e. the Bitcoin network and the Bitcoin Cash network.  ...  Notably, they have been computed after a binning process, considering 50 samples (see [14] for further details). These results indicate that both kinds of networks (i.e.  ... 
doi:10.1145/3211933.3211947 dblp:conf/mobisys/JavaroneW18 fatcat:33rk7ald5bftlbbedi4hfxauhe

Design, Implementation and Simulation of a Cloud Computing System for Enhancing Real-time Video Services by using VANET and Onboard Navigation Systems [article]

Karim Hammoudi, Nabil Ajam, Mohamed Kasraoui, Fadi Dornaika, Karan Radhakrishnan, Karthik Bandi, Qing Cai, Sai Liu
2014 arXiv   pre-print
systems, prominent Cloud Computing Systems (CCSs) and Vehicular Ad-hoc NETwork (VANET).  ...  In this paper, we propose a design for novel and experimental cloud computing systems.  ...  The cloud computing was initially employed through wire-based network for internet and it has been progressively extended to the mobile network (e.g., through cellular networks).  ... 
arXiv:1412.6149v1 fatcat:2q3a34hnjba2pllot5da4lu7xi

Page 160 of American Society of Civil Engineers. Collected Journals Vol. 8, Issue 2 [page]

1994 American Society of Civil Engineers. Collected Journals  
There are many enhance- ments that can be made to this approach, most notably, the maintaining of a number of networks and the crossbreeding of these networks to produce the networks in the new generation  ...  Neural networks do, however, suffer from a number of shortcomings, notably, a lack of precision, limited theory to assist in their design, no guarantee of success in finding an acceptable solution, and  ... 

NetCmpt: a network-based tool for calculating the metabolic competition between bacterial species

Anat Kreimer, Adi Doron-Faigenboim, Elhanan Borenstein, Shiri Freilich
2012 Computer applications in the biosciences : CABIOS  
Availability and implementation: NetCmpt is provided as both a web tool and a software package, designed for the use of non-computational biologists.  ...  consumed substrates (computed as described above) by stepwise addition of those reactions whose substrates are produced in the current core network.  ...  Notably, frequent metabolites (that is participating in more than 10 reactions) as well as water, protons and electron components are removed from the generic network (Kharchenko et al., 2005; Raymond  ... 
doi:10.1093/bioinformatics/bts323 pmid:22668793 fatcat:2br3t2tnircbtf2d3wjdiqsery

EdgeSegNet: A Compact Network for Semantic Segmentation [article]

Zhong Qiu Lin, Brendan Chwyl, Alexander Wong
2019 arXiv   pre-print
A human-machine collaborative design strategy is leveraged to create EdgeSegNet, where principled network design prototyping is coupled with machine-driven design exploration to create networks with customized  ...  In this study, we introduce EdgeSegNet, a compact deep convolutional neural network for the task of semantic segmentation.  ...  Despite these significant advances in deep convolutional neural networks for the task of semantic segmentation over recent years, the high architectural and computational com- plexities of such networks  ... 
arXiv:1905.04222v1 fatcat:q7di5csv3vdnpccig3wbvpsiaq

NetCmpt: a network-based tool for calculating the metabolic competition between bacterial species

A. Kreimer, A. Doron-Faigenboim, E. Borenstein, S. Freilich
2012 Bioinformatics  
Availability and implementation: NetCmpt is provided as both a web tool and a software package, designed for the use of non-computational biologists.  ...  consumed substrates (computed as described above) by stepwise addition of those reactions whose substrates are produced in the current core network.  ...  Notably, frequent metabolites (that is participating in more than 10 reactions) as well as water, protons and electron components are removed from the generic network (Kharchenko et al., 2005; Raymond  ... 
doi:10.1093/bioinformatics/bts522 fatcat:hhx6xdrie5dmnftfy2hum64zva

Understanding principles of integration and segregation using whole-brain computational connectomics: implications for neuropsychiatric disorders

Louis-David Lord, Angus B. Stevner, Gustavo Deco, Morten L. Kringelbach
2017 Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences  
We emphasize how novel methods from network science and whole-brain computational modelling can expand beyond traditional neuroimaging paradigms and help to uncover the neurobiological determinants of  ...  One contribution of 14 to a theme issue 'Mathematical methods in medicine: neuroscience, cardiology and pathology'. describe how the emerging discipline of whole-brain computational connectomics may be  ...  Computational studies have notably shown that different avalanche behaviours are observed as a function of the density of long-range connections in a simulated brain network, and that power-law behaviour  ... 
doi:10.1098/rsta.2016.0283 pmid:28507228 pmcid:PMC5434074 fatcat:ybywypbpevey7fvbiuzuqeceju

802 Standards

Paul Nikolich, Kenneth Christensen, Lori Cameron
2016 Computer  
The creation of the personal computer and the subsequent proliferation of connected machines paved the way for local and global network connectivity, the Internet, mobile computing, smartphones, and the  ...  IEEE standards-notably Ethernet and Wi-Fi-form the basic plumbing of this connectivity.  ... 
doi:10.1109/mc.2016.7 fatcat:zcd5g23mrjb4nf4pj7e7gabzcq

Modeling Socio-Psychological Behaviors in the Era of the WWW: a Brief Overview (poster paper)

Marco Alberto Javarone
2015 International Workshop on Knowledge Discovery on the Web  
In this work, we briefly present some computational models that can be adopted for representing socio-psychological behaviors in this scenario.  ...  Social networks like Facebook strongly speed up the spreading of information among users, and allow people to communicate simultaneously with several individuals.  ...  Notably, our lives are strongly affected by social networks and all devices that are connected on Internet.  ... 
dblp:conf/kdweb/Javarone15 fatcat:mv56tvn2lvcybplc5stf5b7bpy

Improvement of Demand Forecasting Models with Special Days

Cagatay Catal, Ayse Fenerci, Burcak Ozdemir, Onur Gulmez
2015 Procedia Computer Science  
This study shows that good forecasting results can be reached by improving the data even if we do not apply complex computational intelligence techniques.  ...  Although recent studies focused on new computational intelligence techniques for cash demand forecasting, this paper advocates the enhancement of the dataset to improve the prediction performance of forecasting  ...  We know that these notable days have high impact on ATM operations. We worked on several models including different artificial neural network approaches, exponential smoothing, and ARIMA.  ... 
doi:10.1016/j.procs.2015.07.554 fatcat:a5eqpnn2u5ak5ftvlmtwdnupae

A fast-computational spiking neuron model adaptable to any cortical neuron

Ryota Kobayashi, Yasuhiro Tshubo, Shigeru Shinomoto
2009 BMC Neuroscience  
In addition, they require the high computational cost, which hinders performing the simulation of a massively interconnected network.  ...  Both the high flexibility and the low computational cost would help to model the real brain faithfully and examine how network properties may be influenced by the distributed characteristics of component  ...  In addition, they require the high computational cost, which hinders performing the simulation of a massively interconnected network.  ... 
doi:10.1186/1471-2202-10-s1-p22 fatcat:ldhz25gbg5clhm6oaftoivqmu4
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