Hasil Pencarian  ::  Simpan CSV :: Kembali

"This book provides a complete and comprehensive reference/guide to Pyomo (Python Optimization Modeling Objects). The text illustrates the breadth of the modeling and analysis capabilities that are supported by the software and support of complex real-world applications. Pyomo is an open source software package for formulating and solving large-scale optimization and operations research problems. The text begins with a tutorial on simple linear and integer programming models. A detailed reference of Pyomo's modeling components is illustrated with extensive examples, including a discussion of how to load data from data sources like spreadsheets and databases. Chapters describing advanced modeling capabilities for nonlinear and stochastic optimization are also included. The Pyomo software provides familiar modeling features within Python, a powerful dynamic programming language that has a very clear, readable syntax and intuitive object orientation. Pyomo includes Python classes for defining sparse sets, parameters, and variables, which can be used to formulate algebraic expressions that define objectives and constraints. Moreover, Pyomo can be used from a command-line interface and within Python's interactive command environment, which makes it easy to create Pyomo models, apply a variety of optimizers, and examine solutions. The software supports a different modeling approach than commercial AML (Algebraic Modeling Languages) tools, and is designed for flexibility, extensibility, portability, and maintainability but also maintains the central ideas in modern AMLs."

"Prsoses inversi dan forward modeling merupakan proses yang umum dilakukan dalam keilmuan geofisika khususnya pada metode magnetotelurik (MT) untuk memprediksi data dan parameter fisis material batuan di bawah permukaan bumi. Data dalam konteks ini merupakan resistivitas semu dan fase sementara parameter fisis merupakan resistivitas batuan. Proses tersebut biasanya dilakukan dengan menggunakan perangkat lunak tertentu yang perlu di unduh dan di install pada perangkat keras yang memenuhi spesifikasi, hal ini menjadi tidak fleksibel karena perangkat lunak perlu di install ulang jika ingin mengganti perangkat keras dan tidak semua perangkat keras dapat digunakan. Pada penelitian ini penulis mengembangkan platform website berbasis bahasa pemrograman python untuk melakukan proses forward modeling dan inversi data MT 1-D. Forward modeling dilakukan dengan menggunakan persamaan rekursif yang menyatakan hubungan antara impedansi dua lapisan sedangkan inversi dilakukan dengan menggunakan metode Levenberg-Marquardt. Pada inversi dengan stasiun lebih dari 1 maka kurva sounding hasil inversi akan dibentuk menjadi penampang resistivitas bawah permukaan dengan cara Krigging. Secara kuantitatif hasil inversi dengan website memiliki RMS error berkisar 0.08-0.21 % untuk data sintetik dan 0.84-1.84 % untuk data lapangan, secara kualitatif kurva inversi website memiliki trend yang mirip dengan software konvensional sehingga inversi website dinilai cukup valid. Dengan dikembangkannya platform web ini proses inversi dan forward modeling data MT 1-D dapat dilakukan di mana saja melalui perangkat apapun selama terdapat koneksi internet dan browser. Namun karena terdapat perbedan antara penampang hasil inversi website dengan software konvensional yang menyebabkan detil struktur tidak terlihat, maka website ini lebih cocok untuk digunakan pada keperluan akademis untuk melihat pola resistivitas bawah permukan secara umum dan bukan secara detail.

---

Invers and forward modeling is a common process or technique done in the field of geophysics, particularly on magnetotelluric method (MT) in order to predict data and physical parameters of rock materials underneath the surface. Data in this context is apparent resistivity and phase, while physical parameters is the conductivity of the rock materials. This process usually conducted using a certain software that has to be installed on a hardware that meets the minimum requirement, this is not flexible in modern age because the software would need to be re-installed if we wish to use other device, moreover not all device is compatible. In this research, writer is developing a web platform based on python programming language for the purpose of forward and invers modeling of 1-D MT data. The forward modeling algorithm is done by utilizing the recursive equation which states the relationship between impedance of two sequential layers while inverse modeling is done using Levenberg-Marquardt method. In a case where the inverted data has more than 1 station, the sounding curve as the output of the inversion will be made into a resistivity crossection using Krigging. Quantitatively the inversion result using this website has an RMS error of 0.08 - 0.21 % for syntethic data and 0.84 – 1.84 % for real data, qualitatively the inversion curve resulting from this website has similar trend to an inversion curve done by a conventional software, thus the inversion using this website is valid. With the development of this web platform the inverse and forward modeling process of 1-D MT data can be conducted anywhere through all kinds of device as long as internet conection and browser is available. However due to the difference between cross section resulting from inversion using website and using conventional software that has lead to certain structure can not be seen, therefore this website is more suitable to be used in an academic purposes to see subsurface resistivity pattern in general and not in detail."

"Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this book builds your understanding through intuitive explanations and practical examples. You'll explore challenging concepts and practice with applications in computer vision, natural-language processing, and generative models. By the time you finish, you'll have the knowledge and hands-on skills to apply deep learning in your own projects. --"

"Publisher Synopsis1. Introduction. 2. Data Types and Expressions. 3. Control Statements. 4. Strings and Text Files. 5. Lists and Dictionaries. 6. Design with Functions. 7. Simple Graphics and Image Processing. 8. Design with Classes. 9. Graphical User Interfaces. 10. Multithreading, Networks, and Client/Server Programming. 11. Searching, Sorting, and Complexity. (Online only) Appendices. Glossary. Inde"

"The book serves as a first introduction to computer programming of scientific applications, using the high-level Python language. The exposition is example and problem-oriented, where the applications are taken from mathematics, numerical calculus, statistics, physics, biology and finance. The book teaches "Matlab-style" and procedural programming as well as object-oriented programming. High school mathematics is a required background and it is advantageous to study classical and numerical one-variable calculus in parallel with reading this book. Besides learning how to program computers, the reader will also learn how to solve mathematical problems, arising in various branches of science and engineering, with the aid of numerical methods and programming."

"This text serves well as a follow-on text to Python Programming Fundamentalsby Kent D. Lee and published by Springer, but does not require you to have readthat text. In this text the next steps are taken to teach you how to handle largeamounts of data efficiently. A number of algorithms are introduced and the need forthem is motivated through examples that bring meaning to the problems we face ascomputer programmers. An algorithm is a well-defined procedure for accomplishinga task. Algorithms are an important part of Computer Science and this textexplores many algorithms to give you the background you need when writingprograms of your own. The goal is that having seen some of the sorts of algorithms presented in this text, you will be able to apply these techniques to other programs you write in the future."