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Author: Vicki Stracensky
Publisher:
ISBN: 9780692389225
Category :
Languages : en
Pages : 32
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Book Description
"Wise on Weather!" is like getting three books in one:a poem, seasonal safety guide and definitions to 100 weather words - both educational and entertaining. This fun and informative book will hold children's interests for years to come, fostering great learning and enjoyable family time.
Author: Vicki Stracensky
Publisher:
ISBN: 9780692389225
Category :
Languages : en
Pages : 32
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Book Description
"Wise on Weather!" is like getting three books in one:a poem, seasonal safety guide and definitions to 100 weather words - both educational and entertaining. This fun and informative book will hold children's interests for years to come, fostering great learning and enjoyable family time.
Author: Alan Watts
Publisher: Sheridan House, Inc.
ISBN: 1574092669
Category : Nature
Languages : en
Pages : 21
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Book Description
Weather Wise gives you the tools to answer the questions we always ask about the weather. As well as giving us the ins and outs about seasons, cloud formation, rain, wind, hill and mountain weather, thunder, and the development of storms and hurricanes, this handy book will enable you to make your own predictions - what is coming, when it will arrive, and how severe it will be.
Author: Alan Watts
Publisher: A&C Black
ISBN: 1408127083
Category : Sports & Recreation
Languages : en
Pages : 161
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Book Description
Weather Wise is a highly practical, lively and very accessible guide to weather phenomena for anyone who enjoys the outdoors. Suitable for sailors, walkers, climbers, skiers, fishermen, golfers and holidaymakers, it explains how forthcoming weather will affect them, as well as how to predict what is coming and assess how severe it will be. No other weather book has the practical hands-on approach of Alan Watts, whose reputation for explaining complicated meteorological situations in an understandable way for the average reader is second to none. Packed with practical tips, hints and fact panels, it will be a godsend to anyone pursuing an outdoor activity. Covers: the seasons, clouds, heat and cold, rain, changeable weather, showery weather, wind, thunder, fog and mist, sea weather, hill and mountain weather and hurricanes and tornadoes
Author: Vivian Siahaan
Publisher: BALIGE PUBLISHING
ISBN:
Category : Computers
Languages : en
Pages : 196
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Book Description
In this project, we embarked on a journey of exploring time-series weather data and performing forecasting and prediction using Python. The objective was to gain insights into the dataset, visualize feature distributions, analyze year-wise and month-wise patterns, apply ARIMA regression to forecast temperature, and utilize machine learning models to predict weather conditions. Let's delve into each step of the process. To begin, we started by exploring the dataset, which contained historical weather data. We examined the structure and content of the dataset to understand its variables, such as temperature, humidity, wind speed, and weather conditions. Understanding the dataset is crucial for effective analysis and modeling. Next, we visualized the distributions of different features. By creating histograms, box plots, and density plots, we gained insights into the range, central tendency, and variability of the variables. These visualizations allowed us to identify any outliers, skewed distributions, or patterns within the data. Moving on, we explored the dataset's temporal aspects by analyzing year-wise and month-wise distributions. This involved aggregating the data based on years and months and visualizing the trends over time. By examining these patterns, we could observe any long-term or seasonal variations in the weather variables. After gaining a comprehensive understanding of the dataset, we proceeded to apply ARIMA regression for temperature forecasting. ARIMA (Autoregressive Integrated Moving Average) is a powerful technique for time-series analysis. By fitting an ARIMA model to the temperature data, we were able to make predictions and assess the model's accuracy in capturing the underlying patterns. In addition to temperature forecasting, we aimed to predict weather conditions using machine learning models. We employed various classification algorithms such as Logistic Regression, Decision Trees, Random Forests, Support Vector Machines (SVM), K-Nearest Neighbors (KNN), Adaboost, Gradient Boosting, Extreme Gradient Boosting (XGBoost), Light Gradient Boosting (LGBM), and Multi-Layer Perceptron (MLP). These models were trained on the historical weather data, with weather conditions as the target variable. To evaluate the performance of the machine learning models, we utilized several metrics: accuracy, precision, recall, and F1 score. Accuracy measures the overall correctness of the predictions, while precision quantifies the proportion of true positive predictions out of all positive predictions. Recall, also known as sensitivity, measures the ability to identify true positives, and F1 score combines precision and recall into a single metric. Throughout the process, we emphasized the importance of data preprocessing, including handling missing values, scaling features, and splitting the dataset into training and testing sets. Preprocessing ensures the data is in a suitable format for analysis and modeling, and it helps prevent biases or inconsistencies in the results. By following this step-by-step approach, we were able to gain insights into the dataset, visualize feature distributions, analyze temporal patterns, forecast temperature using ARIMA regression, and predict weather conditions using machine learning models. The evaluation metrics provided a comprehensive assessment of the models' performance in capturing the weather conditions accurately. In conclusion, this project demonstrated the power of Python in time-series weather forecasting and prediction. Through data exploration, visualization, regression analysis, and machine learning modeling, we obtained valuable insights and accurate predictions regarding temperature and weather conditions. This knowledge can be applied in various domains such as agriculture, transportation, and urban planning, enabling better decision-making based on weather forecasts.
Author: Mark Moldwin
Publisher: Cambridge University Press
ISBN: 1108791719
Category : Science
Languages : en
Pages : 225
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Book Description
This updated introductory textbook, with added learning features, explains how the Sun influences the Earth and its near-space environment.
Author: Helen Cox Cannons
Publisher: Capstone
ISBN: 1484653343
Category : Juvenile Nonfiction
Languages : en
Pages : 28
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Book Description
Through stunning photographs and simple text, books in this series introduce children to different types of weather. In Thunder and Lightning, children learn about different types of lightning, what thunder and lightning are, what causes lightning, and how to stay safe when thunderstorms occur.
Author: Jenny Offill
Publisher: Vintage
ISBN: 0345806905
Category : Fiction
Languages : en
Pages : 226
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Book Description
NEW YORK TIMES BESTSELLER • From the beloved author of the nationwide best seller Dept. of Speculation comes a “darkly funny and urgent” (NPR) tour de force about a family, and a nation, in crisis. Lizzie works in the library of a university where she was once a promising graduate student. Her side hustle is answering the letters that come in to Hell and High Water, the doom-laden podcast hosted by her former mentor. At first it suits her, this chance to practice her other calling as an unofficial shrink—she has always played this role to her divorced mother and brother recovering from addiction—but soon Lizzie finds herself struggling to strike the obligatory note of hope in her responses. The reassuring rhythms of her life as a wife and mother begin to falter as her obsession with disaster psychology and people preparing for the end of the world grows. A marvelous feat of compression, a mix of great feeling and wry humor, Weather is an electrifying encounter with one of the most gifted writers at work today.
Author: Gail Gibbons
Publisher: Turtleback Books
ISBN: 9780785705475
Category : Weather forecasting
Languages : en
Pages : 0
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Book Description
Describes forecasters at work in a weather station as they use sophisticated equipment to track and gauge the constant changes in the weather
Author: Eric Sloane
Publisher: Courier Corporation
ISBN: 0486443574
Category : Nature
Languages : en
Pages : 98
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Book Description
"Amateur weather forecasters (which includes just about everyone) will find this volume an informative and entertaining account of the why and how of the weather." — The Nation In simple language, Eric Sloane explains the whys and wherefores of weather and weather forecasting — and does it in a style that's universally appealing. With humor and common sense shining through in a book that's also lively and informative, Sloane shows readers how to predict the weather by "reading" such natural phenomena as winds, skies, and animal sounds. This beautifully illustrated and practical treasure trove of climate lore will enlighten outdoorsmen, farmers, sailors, and anyone else who has ever wondered what a large halo around the moon means, why birds "sit it out" before a storm, and whether or not to take an umbrella when leaving the house.
Author: S. S. Bassler
Publisher:
ISBN:
Category : Weather
Languages : en
Pages : 106
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Book Description
