Titlebook: Advances in Computational Intelligence and Communication Technology; Proceedings of CICT Xiao-Zhi Gao,Shailesh Tiwari,Krishn K. Mishra Con

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2194-5357 tems and bioinformatics. As such, it is of interest to research scholars, students, and engineers around the globe.. . .978-981-15-1274-2978-981-15-1275-9Series ISSN 2194-5357 Series E-ISSN 2194-5365

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Thomas Uppenbrink,Sebastian Franklant. The data is then used to create and train a neural network model which is used to predict the power output of the plant given the appropriate input data. This paper demonstrates the training of artificial neural network using environmental and PV module data (module temperature, wind speed and

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https://doi.org/10.1007/978-3-662-69376-6Here we present a computational model that handles this complexity elegantly and efficiently for 8 Ragas (that are typically learned by novice singers). More specifically we show how a relatively simple note transition matrix-based approach incorporating key elements of a Raga’s syntax results in hi

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,Meine Stücke sind Instruktionsstunden, spectrum; (b) Mel frequency cepstral coefficients. Naive Bayes classifier shows best results in speech emotion classification among other classifiers. Emotion data of happy and sad is taken from Surrey Audio-Visual Expressed Emotion (SAVEE) database.

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https://doi.org/10.1007/978-3-662-68966-0e prepared to devise unique base models and fuzzy aggregation module, which is being used to unite these result. The proposed WNFS is created by including the properties of the whale optimization algorithm (WOA) with the neuro-fuzzy architecture. The optimization algorithm selects the appropriate fu

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Advances in Computational Intelligence and Communication Technology978-981-15-1275-9Series ISSN 2194-5357 Series E-ISSN 2194-5365