Literatura académica sobre el tema "SOFT COMPUTING TECHNIQUE"
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Artículos de revistas sobre el tema "SOFT COMPUTING TECHNIQUE"
Yu, Yingbing. "Anomaly Intrusion Detection Based upon Anomalous Events and Soft Computing Technique". International Journal of Machine Learning and Computing 5, n.º 6 (diciembre de 2015): 450–53. http://dx.doi.org/10.18178/ijmlc.2015.5.6.550.
Texto completoSabri, Norlina M., Mazidah Puteh y Mohamad Rusop Mahmood. "Utilization of Soft Computing Techniques in Sputtering Processes: A Review". Advanced Materials Research 832 (noviembre de 2013): 260–65. http://dx.doi.org/10.4028/www.scientific.net/amr.832.260.
Texto completoWong, K. W., P. M. Wong, T. D. Gedeon y C. C. Fung. "Rainfall prediction model using soft computing technique". Soft Computing - A Fusion of Foundations, Methodologies and Applications 7, n.º 6 (1 de mayo de 2003): 434–38. http://dx.doi.org/10.1007/s00500-002-0232-4.
Texto completoKaur, Supreet y Rajiv Mahajan. "Energy efficient clustering protocol for wireless sensor networks". Modern Physics Letters B 32, n.º 32 (20 de noviembre de 2018): 1850400. http://dx.doi.org/10.1142/s0217984918504006.
Texto completoSingh, Dharmpal. "An Effort to Design an Integrated System to Extract Information Under the Domain of Metaheuristics". International Journal of Applied Evolutionary Computation 8, n.º 3 (julio de 2017): 13–52. http://dx.doi.org/10.4018/ijaec.2017070102.
Texto completoSesadri, U., B. Siva Sankar y C. Nagaraju. "Type2 Fuzzy Soft Computing Technique for Image Enhancement". IAES International Journal of Artificial Intelligence (IJ-AI) 4, n.º 3 (1 de septiembre de 2015): 97. http://dx.doi.org/10.11591/ijai.v4.i3.pp97-104.
Texto completoKumarSaini, Dinesh y Jabar H Yousif. "Environmental Scrutinizing System based on Soft Computing Technique". International Journal of Computer Applications 62, n.º 13 (18 de enero de 2013): 45–50. http://dx.doi.org/10.5120/10143-4952.
Texto completoManh, Linh Ho, Francesco Grimaccia, Marco Mussetta y Riccardo E. Zich. "A Soft Computing Hybridization Technique for Antenna Optimization". International Journal on Communications Antenna and Propagation (IRECAP) 5, n.º 1 (28 de febrero de 2015): 16. http://dx.doi.org/10.15866/irecap.v5i1.4899.
Texto completoSudipta Sen, Sudipta Sen. "Hydro-Thermal Scheduling: Using Soft Computing Technique Approch". IOSR Journal of Electrical and Electronics Engineering 5, n.º 6 (2013): 55–80. http://dx.doi.org/10.9790/1676-0565580.
Texto completoGhadiyali, Tejaskumar y Kalpesh Lad. "Risk Minimization in Agribusiness using Soft Computing Technique". IOSR Journal of Computer Engineering 18, n.º 05 (mayo de 2016): 20–25. http://dx.doi.org/10.9790/0661-1805042025.
Texto completoTesis sobre el tema "SOFT COMPUTING TECHNIQUE"
Machaka, Pheeha. "Situation recognition using soft computing techniques". Master's thesis, University of Cape Town, 2012. http://hdl.handle.net/11427/11225.
Texto completoThe last decades have witnessed the emergence of a large number of devices pervasively launched into our daily lives as systems producing and collecting data from a variety of information sources to provide different services to different users via a variety of applications. These include infrastructure management, business process monitoring, crisis management and many other system-monitoring activities. Being processed in real-time, these information production/collection activities raise an interest for live performance monitoring, analysis and reporting, and call for data-mining methods in the recognition, prediction, reasoning and controlling of the performance of these systems by controlling changes in the system and/or deviations from normal operation. In recent years, soft computing methods and algorithms have been applied to data mining to identify patterns and provide new insight into data. This thesis revisits the issue of situation recognition for systems producing massive datasets by assessing the relevance of using soft computing techniques for finding hidden pattern in these systems.
Fernando, Kurukulasuriya Joseph Tilak Nihal. "Soft computing techniques in power system analysis". Thesis, full-text, 2008. https://vuir.vu.edu.au/2025/.
Texto completoFernando, Kurukulasuriya Joseph Tilak Nihal. "Soft computing techniques in power system analysis". full-text, 2008. http://eprints.vu.edu.au/2025/1/thesis.pdf.
Texto completoEsteves, João Trevizoli. "Climate and agrometeorology forecasting using soft computing techniques. /". Jaboticabal, 2018. http://hdl.handle.net/11449/180833.
Texto completoResumo: Precipitação, em pequenas escalas de tempo, é um fenômeno associado a altos níveis de incerteza e variabilidade. Dada a sua natureza, técnicas tradicionais de previsão são dispendiosas e exigentes em termos computacionais. Este trabalho apresenta um modelo para prever a ocorrência de chuvas em curtos intervalos de tempo por Redes Neurais Artificiais (RNAs) em períodos acumulados de 3 a 7 dias para cada estação climática, mitigando a necessidade de predizer o seu volume. Com essa premissa pretende-se reduzir a variância, aumentar a tendência dos dados diminuindo a responsabilidade do algoritmo que atua como um filtro para modelos quantitativos, removendo ocorrências subsequentes de valores de zero(ausência) de precipitação, o que influencia e reduz seu desempenho. O modelo foi desenvolvido com séries temporais de 10 regiões agricolamente relevantes no Brasil, esses locais são os que apresentam as séries temporais mais longas disponíveis e são mais deficientes em previsões climáticas precisas, com 60 anos de temperatura média diária do ar e precipitação acumulada. foram utilizados para estimar a evapotranspiração potencial e o balanço hídrico; estas foram as variáveis utilizadas como entrada para as RNAs. A precisão média para todos os períodos acumulados foi de 78% no verão, 71% no inverno 62% na primavera e 56% no outono, foi identificado que o efeito da continentalidade, o efeito da altitude e o volume da precipitação normal , tem um impacto direto na precisão das RNAs. Os... (Resumo completo, clicar acesso eletrônico abaixo)
Abstract: Precipitation, in short periods of time, is a phenomenon associated with high levels of uncertainty and variability. Given its nature, traditional forecasting techniques are expensive and computationally demanding. This paper presents a model to forecast the occurrence of rainfall in short ranges of time by Artificial Neural Networks(ANNs) in accumulated periods from 3 to 7 days for each climatic season, mitigating the necessity of predicting its amount. With this premise it is intended to reduce the variance, rise the bias of data and lower the responsibility of the model acting as a filter for quantitative models by removing subsequent occurrences of zeros values of rainfall which leads to bias the and reduces its performance. The model were developed with time series from 10 agriculturally relevant regions in Brazil, these places are the ones with the longest available weather time series and and more deficient in accurate climate predictions, it was available 60 years of daily mean air temperature and accumulated precipitation which were used to estimate the potential evapotranspiration and water balance; these were the variables used as inputs for the ANNs models. The mean accuracy of the model for all the accumulated periods were 78% on summer, 71% on winter 62% on spring and 56% on autumn, it was identified that the effect of continentality, the effect of altitude and the volume of normal precipitation, have a direct impact on the accuracy of the ANNs. The models have ... (Complete abstract click electronic access below)
Mestre
Erman, Maria. "Applications of Soft Computing Techniques for Wireless Communications". Licentiate thesis, Blekinge Tekniska Högskola, Institutionen för tillämpad signalbehandling, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-17314.
Texto completoPerez, Ruben E. "Soft Computing techniques and applications in aircraft design optimization". Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2001. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp05/MQ63122.pdf.
Texto completoWang, Lijuan. "Multiphase flow measurement using Coriolis flowmeters incorporating soft computing techniques". Thesis, University of Kent, 2017. https://kar.kent.ac.uk/63877/.
Texto completoYang, Yingjie. "Investigation on soft computing techniques for airport environment evaluation systems". Thesis, Loughborough University, 2008. https://dspace.lboro.ac.uk/2134/35015.
Texto completoAmina, Mahdi. "Dynamic non-linear system modelling using wavelet-based soft computing techniques". Thesis, University of Westminster, 2011. https://westminsterresearch.westminster.ac.uk/item/8zwwz/dynamic-non-linear-system-modelling-using-wavelet-based-soft-computing-techniques.
Texto completoChen, Mingwu. "Motion planning and control of mobile manipulators using soft computing techniques". Thesis, University of Sheffield, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.266128.
Texto completoLibros sobre el tema "SOFT COMPUTING TECHNIQUE"
Chaudhuri, Arindam y Soumya K. Ghosh. Bankruptcy Prediction through Soft Computing based Deep Learning Technique. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-6683-2.
Texto completoBorah, Samarjeet, Ratika Pradhan, Nilanjan Dey y Phalguni Gupta, eds. Soft Computing Techniques and Applications. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-7394-1.
Texto completoTimbadiya, P. V., P. L. Patel, Vijay P. Singh y A. B. Mirajkar, eds. Geospatial and Soft Computing Techniques. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-1901-7.
Texto completoK, Anbumani y Nedunchezhian R, eds. Soft computing applications for database technologies: Techniques and issues. Hershey, PA: Information Science Reference, 2010.
Buscar texto completoPatnaik, Srikanta y Baojiang Zhong, eds. Soft Computing Techniques in Engineering Applications. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-04693-8.
Texto completoPatnaik, Srikanta y Yeon-Mo Yang, eds. Soft Computing Techniques in Vision Science. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-25507-6.
Texto completoPatnaik, Srikanta. Soft Computing Techniques in Vision Science. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.
Buscar texto completoE, Ruano A. y Institution of Electrical Engineers, eds. Intelligent control systems using computational intelligence techniques. London: Institution of Electrical Engineers, 2005.
Buscar texto completoK, Pal Sankar, Polkowski Lech y Skowron Andrzej, eds. Rough-neural computing: Techniques for computing with words. Berlin: Springer, 2004.
Buscar texto completoChakraborty, Kabir y Abhijit Chakrabarti. Soft Computing Techniques in Voltage Security Analysis. New Delhi: Springer India, 2015. http://dx.doi.org/10.1007/978-81-322-2307-8.
Texto completoCapítulos de libros sobre el tema "SOFT COMPUTING TECHNIQUE"
Rotaru, Florin, Silviu-Ioan Bejinariu, Cristina Diana Niţă, Ramona Luca, Mihaela Luca y Adrian Ciobanu. "Retinal Vessel Classification Technique". En Soft Computing Applications, 498–514. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-62524-9_37.
Texto completoJara-Maldonado, Miguel, Vicente Alarcon-Aquino y Roberto Rosas-Romero. "A Multiresolution Machine Learning Technique to Identify Exoplanets". En Advances in Soft Computing, 50–64. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-60884-2_4.
Texto completoSelouani, Sid-Ahmed. "Variance of the Reconstruction Error Technique". En Speech Processing and Soft Computing, 25–32. New York, NY: Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4419-9685-5_4.
Texto completoSarwar, Sohail, Zia Ul-Qayyum y Owais Ahmed Malik. "CBR and Neural Networks Based Technique for Predictive Prefetching". En Advances in Soft Computing, 221–32. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16773-7_19.
Texto completoKazikova, Anezka, Michal Pluhacek, Adam Viktorin y Roman Senkerik. "New Running Technique for the Bison Algorithm". En Artificial Intelligence and Soft Computing, 417–26. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-91253-0_39.
Texto completoPankwar, Deepak, G. L. Saini, Pankaj Agarwal y Pardeep Singh. "Firefly Optimization Technique for Software Quality Prediction". En Soft Computing: Theories and Applications, 263–73. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-0707-4_25.
Texto completoSingh, Ashwini y A. B. Mirajkar. "Leakage Management in WDN System Using Optimization Technique". En Geospatial and Soft Computing Techniques, 345–56. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-1901-7_28.
Texto completoSoni, Ashu y Maneesha Gupta. "Fractional Order Elliptic Filter Implemented Using Optimization Technique". En Cognitive Informatics and Soft Computing, 181–93. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-1056-1_16.
Texto completoJoon, Kirti, Namrata Agrawal, Hifzan Ahmad, Vikash Yadav, Dinesh Kumar Sah y Cornel Barna. "DDoS Attack Prevention Protocol Through Support Vector Machine and Fuzzy Clustering Mechanism on Traffic Flow with Harmonic Homogeneity Validation Technique". En Soft Computing Applications, 197–214. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-51992-6_17.
Texto completoOnisawa, Takehisa. "Soft Computing Technique in Kansei (Emotional) Information Processing". En Soft Computing and Human-Centered Machines, 215–48. Tokyo: Springer Japan, 2000. http://dx.doi.org/10.1007/978-4-431-67907-3_9.
Texto completoActas de conferencias sobre el tema "SOFT COMPUTING TECHNIQUE"
Reddy, G. Deepika, N. R. Medikondu, T. Vijaya Kumar, M. B. S. Sreekara Reddy, P. Harisha y M. Murali Krishna. "Soft computing technique for jobs scheduling". En 2ND INTERNATIONAL CONFERENCE ON ADVANCED INFORMATION SCIENTIFIC DEVELOPMENT (ICAISD) 2021: Innovating Scientific Learning for Deep Communication. AIP Publishing, 2023. http://dx.doi.org/10.1063/5.0143070.
Texto completoBarbu, Tudor, Mihaela Costin y Adrian Ciobanu. "Content-based image recognition technique using area moments". En 2010 4th International Workshop on Soft Computing Applications (SOFA). IEEE, 2010. http://dx.doi.org/10.1109/sofa.2010.5565603.
Texto completoSingh, J. Amar Pratap y M. Karnan. "Intelligent Location Management Using Soft Computing Technique". En 2010 Second International Conference on Communication Software and Networks. IEEE, 2010. http://dx.doi.org/10.1109/iccsn.2010.60.
Texto completoGoel, Shubham, Amrendra Tripathi, Tanupriya Choudhury y Vivek Kumar. "Parkinson's Disease Detection using Soft Computing Technique". En 2019 8th International Conference System Modeling and Advancement in Research Trends (SMART). IEEE, 2019. http://dx.doi.org/10.1109/smart46866.2019.9117384.
Texto completoMishra, Arvind Kumar, Renuka Nagpal, Kirti Seth y Rajni Sehgal. "Analyzability of SOA using Soft Computing Technique". En 2022 10th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO). IEEE, 2022. http://dx.doi.org/10.1109/icrito56286.2022.9964602.
Texto completoBarbu, Tudor, Mihaela Costin y Adrian Ciobanu. "Histogram intersection based image retrieval technique using relevance feedback". En 2009 3rd International Workshop on Soft Computing Applications (SOFA). IEEE, 2009. http://dx.doi.org/10.1109/sofa.2009.5254878.
Texto completoGe Zheng, Qinghua Cao y Chao Liu. "Anomaly intrusion detection based on soft computing technique". En 2011 International Conference on System Science, Engineering Design and Manufacturing Informatization (ICSEM). IEEE, 2011. http://dx.doi.org/10.1109/icssem.2011.6081303.
Texto completoEsther, J. y M. Mohamed Sathik. "Retrieval of Brain Image Using Soft Computing Technique". En 2014 International Conference on Intelligent Computing Applications (ICICA). IEEE, 2014. http://dx.doi.org/10.1109/icica.2014.104.
Texto completoHota, Radhanath, Sachikanta Dash, Sujogya Mishra, Sipali Pradhan y P. K. Pattnaik. "Symptoms Prediction of Tuberculosis using Soft Computing Technique". En 2022 OITS International Conference on Information Technology (OCIT). IEEE, 2022. http://dx.doi.org/10.1109/ocit56763.2022.00071.
Texto completoParekh, Aarti M. y Nidhi B. Shah. "Classification of ovarian cyst using soft computing technique". En 2017 8th International Conference on Computing, Communication and Networking Technologies (ICCCNT). IEEE, 2017. http://dx.doi.org/10.1109/icccnt.2017.8203965.
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