000827107 000__ 05075cam\a2200541Ii\4500 000827107 001__ 827107 000827107 005__ 20230306144438.0 000827107 006__ m\\\\\o\\d\\\\\\\\ 000827107 007__ cr\cn\nnnunnun 000827107 008__ 180323t20182018sz\a\\\\ob\\\\101\0\eng\d 000827107 020__ $$a9789811078682$$q(electronic book) 000827107 020__ $$a9811078688$$q(electronic book) 000827107 020__ $$z9789811078675 000827107 035__ $$aSP(OCoLC)on1029352647 000827107 035__ $$aSP(OCoLC)1029352647 000827107 040__ $$aN$T$$beng$$erda$$epn$$cN$T$$dN$T$$dGW5XE$$dEBLCP$$dOCLCF$$dMERER 000827107 049__ $$aISEA 000827107 050_4 $$aQ334 000827107 08204 $$a006.3$$223 000827107 1112_ $$aInternational Conference on Artificial Intelligence and Evolutionary Computations in Engineering Systems$$d(2017 :$$cMadanapalle, India) 000827107 24510 $$aArtificial intelligence and evolutionary computations in engineering systems :$$bproceedings of ICAIECES 2017 /$$cSubhransu Sekhar Dash, Paruchuri Chandra Babu Naidu, Ramazan Bayindir, Swagatam Das, editors. 000827107 2463_ $$aICAIECES 2017 000827107 264_1 $$aCham, Switzerland :$$bSpringer,$$c[2018] 000827107 264_4 $$c©2018 000827107 300__ $$a1 online resource :$$billustrations. 000827107 336__ $$atext$$btxt$$2rdacontent 000827107 337__ $$acomputer$$bc$$2rdamedia 000827107 338__ $$aonline resource$$bcr$$2rdacarrier 000827107 4901_ $$aAdvances in intelligent systems and computing,$$x2194-5357 ;$$vvolume 668 000827107 504__ $$aIncludes bibliographical references and index. 000827107 5050_ $$aIntro; Preface; Contents; About the Editors; 1 Testing the Functionality of Firewall in Software-Defined Networking; Abstract; 1 Introduction; 2 Firewall; 3 OpenFlow Protocol; 4 Methodology; 5 Experimental Set-Up; 6 Result and Discussion; 6.1 Scenario 1; 6.2 Scenario 2; 6.3 Scenario 3; 7 Latency and Throughput; 8 Conclusion; References; 2 An Extension of 2D Laplacian of Gaussian (LoG)-Based Spot Detection Method to 3D; Abstract; 1 Introduction; 2 Methodology; 2.1 Original 2D Laplacian of Gaussian (LoG); 2.2 3D Laplacian of Gaussian (LoG); 2.3 3D Synthetic Image Datasets 000827107 5058_ $$a2.4 Performance Measures3 Experimental Results; 4 Conclusions; Bibliography; 3 Distributive MPPT Approach Using ANFIS and Perturb&Observe Techniques Under Uniform and Partial Shading Conditions; Abstract; 1 Introduction; 2 MPPT Techniques; 2.1 Perturb&Observe (P&O) Technique; 2.2 Adaptive Neuro-Fuzzy Inference System (ANFIS); 2.3 Series-Connected Distributed Maximum Power Point Tracking (DMPPT); 3 Simulation Model; 4 Results and Discussion; 5 Conclusion; References; 4 Performance of MPPT in Photovoltaic Systems Using GA-ANN Optimization Scheme; Abstract; 1 Introduction; 2 Related Works 000827107 5058_ $$a3 Proposed Model3.1 Modeling of Buck-Boost DC-to-DC Converter; 3.2 Artificial Neural Network Maximum Power Point Tracking Controller (ANN-MPPT); 3.3 Genetic Algorithm Maximum Power Point Tracking Controller (GA-MPPT); 4 Simulation and Numerical Results; 5 Conclusion; References; 5 The Use of Multilayer Perceptron to Classify and Locate Power Transmission Line Faults; Abstract; 1 Introduction; 2 Experimental Setup; 3 Experimental Results; 4 Conclusions; References; 6 Generation of 3D Realistic Synthetic Image Datasets for Spot Detection Evaluation; Abstract; 1 Introduction; 1.1 Previous Work 000827107 5058_ $$a2 Simulation Framework2.1 Background Modelling; 2.2 Spot Appearance; 2.3 Noise Generation; 2.4 Signal-to-Noise Ratio; 3 Experimental Set-up; 3.1 Synthetic Images; 3.2 Evaluation; 4 Experimental Results; 5 Conclusions; Acknowledgements; References; 7 Modified Newton's Method in the Leapfrog Method for Mobile Robot Path Planning; Abstract; 1 Introduction; 2 Optimal Control; 2.1 Leapfrog Method; 2.2 Modified Newton's Method; 3 Simulation Results; 4 Conclusion and Future Work; Bibliography; 8 Impact of Poor Data Quality in Remotely Sensed Data; Abstract; 1 Introduction; 2 Missing Data Techniques 000827107 5058_ $$a2.1 Listwise Deletion2.2 Mean-Mode Imputation; 2.3 Nearest Neighbour Imputation; 2.4 Regression Imputation; 3 Machine Learning Techniques; 3.1 Random Forest; 3.2 k-nearest Neighbour; 3.3 Artificial Neural Networks; 3.4 Support Vector Machines; 4 Study Methodology; 4.1 Experimental Set-up; 4.2 Experimental Results; 5 Conclusion; Acknowledgements; References; 9 Image Enrichment Using Single Discrete Wavelet Transform Multi-resolution and Frequency Partition; Abstract; 1 Introduction; 1.1 Image Fusion; 1.2 Standard Image Fusion Methods; 2 DCT-Frequency Partition; 2.1 Procedure for DCT-FP 000827107 506__ $$aAccess limited to authorized users. 000827107 588__ $$aOnline resource; title from PDF title page (viewed March 26, 2018). 000827107 650_0 $$aArtificial intelligence$$vCongresses. 000827107 650_0 $$aComputational intelligence$$vCongresses. 000827107 7001_ $$aDash, Subhransu Sekhar,$$eeditor. 000827107 7001_ $$aNaidu, Paruchuri Chan Babu,$$eeditor. 000827107 7001_ $$aBayindir, Ramazan,$$eeditor. 000827107 7001_ $$aDas, Swagatam,$$eeditor. 000827107 830_0 $$aAdvances in intelligent systems and computing ;$$v668. 000827107 852__ $$bebk 000827107 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-981-10-7868-2$$zOnline Access$$91397441.1 000827107 909CO $$ooai:library.usi.edu:827107$$pGLOBAL_SET 000827107 980__ $$aEBOOK 000827107 980__ $$aBIB 000827107 982__ $$aEbook 000827107 983__ $$aOnline 000827107 994__ $$a92$$bISE