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Artykuły w czasopismach na temat "SOFT COMPUTING TECHNIQUE"
Yu, Yingbing. "Anomaly Intrusion Detection Based upon Anomalous Events and Soft Computing Technique". International Journal of Machine Learning and Computing 5, nr 6 (grudzień 2015): 450–53. http://dx.doi.org/10.18178/ijmlc.2015.5.6.550.
Pełny tekst źródłaSabri, Norlina M., Mazidah Puteh i Mohamad Rusop Mahmood. "Utilization of Soft Computing Techniques in Sputtering Processes: A Review". Advanced Materials Research 832 (listopad 2013): 260–65. http://dx.doi.org/10.4028/www.scientific.net/amr.832.260.
Pełny tekst źródłaWong, K. W., P. M. Wong, T. D. Gedeon i C. C. Fung. "Rainfall prediction model using soft computing technique". Soft Computing - A Fusion of Foundations, Methodologies and Applications 7, nr 6 (1.05.2003): 434–38. http://dx.doi.org/10.1007/s00500-002-0232-4.
Pełny tekst źródłaKaur, Supreet, i Rajiv Mahajan. "Energy efficient clustering protocol for wireless sensor networks". Modern Physics Letters B 32, nr 32 (20.11.2018): 1850400. http://dx.doi.org/10.1142/s0217984918504006.
Pełny tekst źródłaSingh, Dharmpal. "An Effort to Design an Integrated System to Extract Information Under the Domain of Metaheuristics". International Journal of Applied Evolutionary Computation 8, nr 3 (lipiec 2017): 13–52. http://dx.doi.org/10.4018/ijaec.2017070102.
Pełny tekst źródłaSesadri, U., B. Siva Sankar i C. Nagaraju. "Type2 Fuzzy Soft Computing Technique for Image Enhancement". IAES International Journal of Artificial Intelligence (IJ-AI) 4, nr 3 (1.09.2015): 97. http://dx.doi.org/10.11591/ijai.v4.i3.pp97-104.
Pełny tekst źródłaKumarSaini, Dinesh, i Jabar H Yousif. "Environmental Scrutinizing System based on Soft Computing Technique". International Journal of Computer Applications 62, nr 13 (18.01.2013): 45–50. http://dx.doi.org/10.5120/10143-4952.
Pełny tekst źródłaManh, Linh Ho, Francesco Grimaccia, Marco Mussetta i Riccardo E. Zich. "A Soft Computing Hybridization Technique for Antenna Optimization". International Journal on Communications Antenna and Propagation (IRECAP) 5, nr 1 (28.02.2015): 16. http://dx.doi.org/10.15866/irecap.v5i1.4899.
Pełny tekst źródłaSudipta Sen, Sudipta Sen. "Hydro-Thermal Scheduling: Using Soft Computing Technique Approch". IOSR Journal of Electrical and Electronics Engineering 5, nr 6 (2013): 55–80. http://dx.doi.org/10.9790/1676-0565580.
Pełny tekst źródłaGhadiyali, Tejaskumar, i Kalpesh Lad. "Risk Minimization in Agribusiness using Soft Computing Technique". IOSR Journal of Computer Engineering 18, nr 05 (maj 2016): 20–25. http://dx.doi.org/10.9790/0661-1805042025.
Pełny tekst źródłaRozprawy doktorskie na temat "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.
Pełny tekst źródłaThe 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/.
Pełny tekst źródłaFernando, Kurukulasuriya Joseph Tilak Nihal. "Soft computing techniques in power system analysis". full-text, 2008. http://eprints.vu.edu.au/2025/1/thesis.pdf.
Pełny tekst źródłaEsteves, João Trevizoli. "Climate and agrometeorology forecasting using soft computing techniques. /". Jaboticabal, 2018. http://hdl.handle.net/11449/180833.
Pełny tekst źródłaResumo: 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.
Pełny tekst źródłaPerez, 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.
Pełny tekst źródłaWang, Lijuan. "Multiphase flow measurement using Coriolis flowmeters incorporating soft computing techniques". Thesis, University of Kent, 2017. https://kar.kent.ac.uk/63877/.
Pełny tekst źródłaYang, Yingjie. "Investigation on soft computing techniques for airport environment evaluation systems". Thesis, Loughborough University, 2008. https://dspace.lboro.ac.uk/2134/35015.
Pełny tekst źródłaAmina, 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.
Pełny tekst źródłaChen, 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.
Pełny tekst źródłaKsiążki na temat "SOFT COMPUTING TECHNIQUE"
Chaudhuri, Arindam, i 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.
Pełny tekst źródłaBorah, Samarjeet, Ratika Pradhan, Nilanjan Dey i Phalguni Gupta, red. Soft Computing Techniques and Applications. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-7394-1.
Pełny tekst źródłaTimbadiya, P. V., P. L. Patel, Vijay P. Singh i A. B. Mirajkar, red. Geospatial and Soft Computing Techniques. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-1901-7.
Pełny tekst źródłaK, Anbumani, i Nedunchezhian R, red. Soft computing applications for database technologies: Techniques and issues. Hershey, PA: Information Science Reference, 2010.
Znajdź pełny tekst źródłaPatnaik, Srikanta, i Baojiang Zhong, red. Soft Computing Techniques in Engineering Applications. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-04693-8.
Pełny tekst źródłaPatnaik, Srikanta, i Yeon-Mo Yang, red. Soft Computing Techniques in Vision Science. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-25507-6.
Pełny tekst źródłaPatnaik, Srikanta. Soft Computing Techniques in Vision Science. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.
Znajdź pełny tekst źródłaE, Ruano A., i Institution of Electrical Engineers, red. Intelligent control systems using computational intelligence techniques. London: Institution of Electrical Engineers, 2005.
Znajdź pełny tekst źródłaK, Pal Sankar, Polkowski Lech i Skowron Andrzej, red. Rough-neural computing: Techniques for computing with words. Berlin: Springer, 2004.
Znajdź pełny tekst źródłaChakraborty, Kabir, i 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.
Pełny tekst źródłaCzęści książek na temat "SOFT COMPUTING TECHNIQUE"
Rotaru, Florin, Silviu-Ioan Bejinariu, Cristina Diana Niţă, Ramona Luca, Mihaela Luca i Adrian Ciobanu. "Retinal Vessel Classification Technique". W Soft Computing Applications, 498–514. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-62524-9_37.
Pełny tekst źródłaJara-Maldonado, Miguel, Vicente Alarcon-Aquino i Roberto Rosas-Romero. "A Multiresolution Machine Learning Technique to Identify Exoplanets". W Advances in Soft Computing, 50–64. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-60884-2_4.
Pełny tekst źródłaSelouani, Sid-Ahmed. "Variance of the Reconstruction Error Technique". W 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.
Pełny tekst źródłaSarwar, Sohail, Zia Ul-Qayyum i Owais Ahmed Malik. "CBR and Neural Networks Based Technique for Predictive Prefetching". W Advances in Soft Computing, 221–32. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16773-7_19.
Pełny tekst źródłaKazikova, Anezka, Michal Pluhacek, Adam Viktorin i Roman Senkerik. "New Running Technique for the Bison Algorithm". W Artificial Intelligence and Soft Computing, 417–26. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-91253-0_39.
Pełny tekst źródłaPankwar, Deepak, G. L. Saini, Pankaj Agarwal i Pardeep Singh. "Firefly Optimization Technique for Software Quality Prediction". W Soft Computing: Theories and Applications, 263–73. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-0707-4_25.
Pełny tekst źródłaSingh, Ashwini, i A. B. Mirajkar. "Leakage Management in WDN System Using Optimization Technique". W Geospatial and Soft Computing Techniques, 345–56. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-1901-7_28.
Pełny tekst źródłaSoni, Ashu, i Maneesha Gupta. "Fractional Order Elliptic Filter Implemented Using Optimization Technique". W Cognitive Informatics and Soft Computing, 181–93. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-1056-1_16.
Pełny tekst źródłaJoon, Kirti, Namrata Agrawal, Hifzan Ahmad, Vikash Yadav, Dinesh Kumar Sah i Cornel Barna. "DDoS Attack Prevention Protocol Through Support Vector Machine and Fuzzy Clustering Mechanism on Traffic Flow with Harmonic Homogeneity Validation Technique". W Soft Computing Applications, 197–214. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-51992-6_17.
Pełny tekst źródłaOnisawa, Takehisa. "Soft Computing Technique in Kansei (Emotional) Information Processing". W Soft Computing and Human-Centered Machines, 215–48. Tokyo: Springer Japan, 2000. http://dx.doi.org/10.1007/978-4-431-67907-3_9.
Pełny tekst źródłaStreszczenia konferencji na temat "SOFT COMPUTING TECHNIQUE"
Reddy, G. Deepika, N. R. Medikondu, T. Vijaya Kumar, M. B. S. Sreekara Reddy, P. Harisha i M. Murali Krishna. "Soft computing technique for jobs scheduling". W 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.
Pełny tekst źródłaBarbu, Tudor, Mihaela Costin i Adrian Ciobanu. "Content-based image recognition technique using area moments". W 2010 4th International Workshop on Soft Computing Applications (SOFA). IEEE, 2010. http://dx.doi.org/10.1109/sofa.2010.5565603.
Pełny tekst źródłaSingh, J. Amar Pratap, i M. Karnan. "Intelligent Location Management Using Soft Computing Technique". W 2010 Second International Conference on Communication Software and Networks. IEEE, 2010. http://dx.doi.org/10.1109/iccsn.2010.60.
Pełny tekst źródłaGoel, Shubham, Amrendra Tripathi, Tanupriya Choudhury i Vivek Kumar. "Parkinson's Disease Detection using Soft Computing Technique". W 2019 8th International Conference System Modeling and Advancement in Research Trends (SMART). IEEE, 2019. http://dx.doi.org/10.1109/smart46866.2019.9117384.
Pełny tekst źródłaMishra, Arvind Kumar, Renuka Nagpal, Kirti Seth i Rajni Sehgal. "Analyzability of SOA using Soft Computing Technique". W 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.
Pełny tekst źródłaBarbu, Tudor, Mihaela Costin i Adrian Ciobanu. "Histogram intersection based image retrieval technique using relevance feedback". W 2009 3rd International Workshop on Soft Computing Applications (SOFA). IEEE, 2009. http://dx.doi.org/10.1109/sofa.2009.5254878.
Pełny tekst źródłaGe Zheng, Qinghua Cao i Chao Liu. "Anomaly intrusion detection based on soft computing technique". W 2011 International Conference on System Science, Engineering Design and Manufacturing Informatization (ICSEM). IEEE, 2011. http://dx.doi.org/10.1109/icssem.2011.6081303.
Pełny tekst źródłaEsther, J., i M. Mohamed Sathik. "Retrieval of Brain Image Using Soft Computing Technique". W 2014 International Conference on Intelligent Computing Applications (ICICA). IEEE, 2014. http://dx.doi.org/10.1109/icica.2014.104.
Pełny tekst źródłaHota, Radhanath, Sachikanta Dash, Sujogya Mishra, Sipali Pradhan i P. K. Pattnaik. "Symptoms Prediction of Tuberculosis using Soft Computing Technique". W 2022 OITS International Conference on Information Technology (OCIT). IEEE, 2022. http://dx.doi.org/10.1109/ocit56763.2022.00071.
Pełny tekst źródłaParekh, Aarti M., i Nidhi B. Shah. "Classification of ovarian cyst using soft computing technique". W 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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