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Temporal data mining using genetic algorithm and neural network —A case study of air pollutant forecasts

Shine-Wei Lin, Chih-Hong Sun, Chin-Han Chen
2004 Geo-spatial Information Science  
Therefore this paper integrated genetic algorithm and neural network techniques to build new temporal predicting analysis tools for Geographic Information System (GIS).  ...  Artificial intelligence technology like neural network and genetic algorithm can easily cope with highly complicated and non-linear combined spatial and temporal issues.  ...  Artificial intelligent technology modules Step5: Select, using genetic algorithms and neural network as the model of air pollutants forecast Step6: Adjust the parameters of the genetic algorithms (the  ... 
doi:10.1007/bf02826674 fatcat:ds4yyw7dk5fmfcnywqmav5xbne

Scale Independence in the Visual System [chapter]

Raul C. Muresan
2004 Studies in Fuzziness and Soft Computing  
even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use.  ...  © Springer-Verlag Berlin Heidelberg 2004 Softcover reprint of the hardcover 1st edition 2004 The use of general descriptive names, registered names trademarks, etc. in this publication does not imply,  ...  neural networks and use of artificial neural networks to sol ve real world problems.  ... 
doi:10.1007/978-3-540-39935-3_1 fatcat:ndxvzjuncjhhthkbw4bcbumxem

Multi-grid cellular genetic algorithm for optimizing variable ordering of ROBDDs

Cristian Rotaru, Octav Brudaru
2012 2012 IEEE Congress on Evolutionary Computation  
The approach systematically produces better results than the used basic genetic algorithm and better or similar results with other heuristic methods.  ...  The extensive experimental evaluation uses difficult classical benchmarks and proves the efficiency and the stability of the algorithm.  ...  for Neural Networks 247, Glenn Francis and Sandra Stein, Prediction of Histologic Grade in Breast Cancer using an Artificial Neural Network. 266, Yozo Suzuki, Michimasa Kitahara and Masaki Kobayashi,  ... 
doi:10.1109/cec.2012.6256590 dblp:conf/cec/RotaruB12 fatcat:4ly3nrktw5habc6lf5err7d5py

Table of Contents

2020 2020 IEEE Symposium Series on Computational Intelligence (SSCI)  
Time Series Forecasting with Temporal Attention Convolutional Neural Networks Leonardos Pantiskas, Kees Verstoep and Henri Bal .......... 1687 Online System Identification for Nonlinear Uncertain Dynamical  ...  .......... 281 Using Neural Networks and Diversifying Differential Evolution for Dynamic Optimisation Maryam Hasani Shoreh, Renato Hermoza Aragones and Frank Neumann .......... 289 Responsive Multi-population  ... 
doi:10.1109/ssci47803.2020.9308155 fatcat:hyargfnk4vevpnooatlovxm4li

A survey on ecg signal monitoring through sensor and prediction of heart attack with the help of optimized neural network using genetic algorithm

2016 International Journal of Latest Trends in Engineering and Technology  
Neural Network is widely used tool for predicting heart diseases diagnosis. A Heart Disease Prediction System is developed using Neural Network and Genetic Algorithm.  ...  OBJECTIVES: The major objective of this research is to monitor heart related activity using ECG sensor for prediction of heart attack using optimized neural network using genetic algorithm and enhance  ... 
doi:10.21172/1.81.019 fatcat:7i26g3ga5bectgjx3jq5wf4jku

THE SURVEY OF SOFT COMPUTING TECHNIQUES FOR RELIABILITY PREDICTION

Jarosław Smoczek
2015 Journal of KONES Powertrain and Transport  
The artificial intelligence is frequently addressed to the predictive problem by utilizing the learning capability of artificial neural network (ANN), and possibility of nonlinear mapping using fuzzy rules-based  ...  system (FRBS) or recognizing and optimizing data-derived pattern by using evolutionary algorithms.  ...  The prediction model was offline and online tested with use of time-series algorithms and the artificial neural network.  ... 
doi:10.5604/12314005.1138154 fatcat:rpenk3etgbc2dgsza6ula6otwq

Artificial Intelligence in Civil Engineering

Pengzhen Lu, Shengyong Chen, Yujun Zheng
2012 Mathematical Problems in Engineering  
This paper summarizes recently developed methods and theories in the developing direction for applications of artificial intelligence in civil engineering, including evolutionary computation, neural networks  ...  , fuzzy systems, expert system, reasoning, classification, and learning, as well as others like chaos theory, cuckoo search, firefly algorithm, knowledge-based engineering, and simulated annealing.  ...  , and multi-stage objective functions.  ... 
doi:10.1155/2012/145974 fatcat:asd3grpoabf5xn6tdpctxkxtwy

Ecological Model of Groundwater Environment Based on Hybrid Soft Computing Method

2017 Revista Técnica de la Facultad de Ingeniería Universidad del Zulia  
algorithm optimization, and it's includes the difference evolution algorithm and the neural network module.  ...  The experimental results show that there is no significant positive correlation between the correlation of the samples and the prediction accuracy, while the network structure and the representation of  ...  In this paper, DE-BP artificial neural network is established by using DE algorithm and neural network (Quiroga and Popescu,2013) .  ... 
doi:10.21311/001.39.10.43 fatcat:4xo6qlcx2vax7frtibbodni3q4

Applications of Soft Computing in Civil Engineering: A Review

Vinay Chandwani, Vinay Agrawal, Ravindra Nagar
2013 International Journal of Computer Applications  
The review paper presents the applications of two major Soft Computing techniques viz., Artificial Neural Networks and Genetic Algorithms in the field of Civil Engineering, which to some extent has replaced  ...  Genetic Algorithms and Fuzzy Logic.  ...  Networks and Genetic Algorithms.  ... 
doi:10.5120/14047-2210 fatcat:ed46xbfhufbdjpdaal6zk4ozoe

Visual Sensation and Perception Computational Models for Deep Learning: State of the art, Challenges and Prospects [article]

Bing Wei, Yudi Zhao, Kuangrong Hao, Lei Gao
2021 arXiv   pre-print
Finally, this paper also summarizes the current challenges of visual perception and predicts its future development trends.  ...  Computational models inspired by visual perception have the characteristics of complexity and diversity, as they come from many subjects such as cognition science, information science, and artificial intelligence  ...  Besides, an adaptive visual interaction mechanism is used in DNN for multi-target dynamic state prediction in a real traffic environment [81] . Furthermore, Wei et al.  ... 
arXiv:2109.03391v1 fatcat:xtgda2x6azd2laun45tqfj77gi

A Survey on Recurrent Neural Network Based Modelling of Gene Regulatory Network

Sudip Mandal
2016 MOJ Proteomics & Bioinformatics  
Among the different popular models to infer GRN, Recurrent Neural Networks (RNN) are considered as most popular and promising mathematical tool to model the dynamics of, as well as to infer the correct  ...  It is observed that finding out the most suitable and efficient optimization techniques for the accurate inference of small artificial, large artificial, Dream4 Network, and real world GRNs with less computational  ...  RNN [21] which is a closed loop Neural Network with a delayed feedback variable, and it is suitable to model genetic system dynamics from temporal data.  ... 
doi:10.15406/mojpb.2016.04.00125 fatcat:htwayj2gvvchjboobxnbqi5tye

Paper Titles

2020 2020 3rd International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)  
using Artificial Neural Network Roadside Unit Power Saving using Vehicle Detection System in Vehicular Ad-hoc Network Robust Control Design Procedure and Simulation of PRES Controller having Phase-Locked  ...  H I L M N O P Q R S T U V W A bio-motivated vision system and artificial neural network for autonomous UAV obstacle avoidance A Combination of Defected Ground Structure and Line Resonator for Mutual  ... 
doi:10.1109/isriti51436.2020.9315349 fatcat:7lctjs3x45apfgec42ra4u7l2e

Hybrid learning machines

Ajith Abraham, Emilio Corchado, Juan M. Corchado
2009 Neurocomputing  
The algorithm is based on a Paretobased multi-objective genetic algorithm, with a special crossover operator that uses clustering validation measures as objective functions.  ...  This hybrid system facilitates the intrusion detection in dynamic networks, in a more flexible and adaptable manner.  ... 
doi:10.1016/j.neucom.2009.02.017 fatcat:jatayx5ec5h5hd72bjrlw2mhie

Program

2009 2009 International Joint Conference on Neural Networks  
P1421 Synthesis of Crossed Dipole Frequency Selective Surfaces Using Genetic Algorithms and Artificial Neural Networks Rossana Cruz, Paulo Silva and Adaildo D'Assuncao P1422 Learning on Class Imbalanced  ...  Gaweda, Room: South Hall-Atlanta Merchandise Mart P1101 Using an Artificial Neural Network to Predict Necrotizing Enterocolitis in Premature Infants Martina Mueller, Sarah Taylor, Carol Wagner and Jonas  ... 
doi:10.1109/ijcnn.2009.5178575 fatcat:kxaceopferd23ps5uyrn3m7xjy

Solar radiation: Cloudiness forecasting using a soft computing approach

Vassiliki H. Mantzari, Dimitrios H. Mantzaris
2012 Artificial intelligence research  
Artificial Neural Networks, Fuzzy Logic, Evolutionary Programming, Genetic Algorithms, Mimetic Algorithms and Artificial Immune Systems are subfields of soft computing.  ...  The combination of meteorological and temporal parameters as inputs of the proposed artificial neural system results the development of an artificial neural technique for the cloudiness prediction, instead  ...  results using different artificial neural network architectures.  ... 
doi:10.5430/air.v2n1p69 fatcat:f4v657panjdozcrt6oaebryohy
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