Personalized real time weather forecasting

Temperature forecasting and rain forecasting in today's environment is playing a major role in many fields like transportation, tour planning and agriculture. The purpose of this paper is to provide a real time forecasting to the user according to their current position and requirement. The simplest method of forecasting the weather, persistence, relies upon today's conditions to forecast the conditions tomorrow i.e. analyzing historical data for predicting future weather conditions. The weather data used for the DM research include daily temperature, daily pressure and monthly rainfall.

Comments: Published in IJACSA 5 pages Weather Forcasting. Paper 26

Similar Publications

In our previous work we reported on a linked-courses learning community for underrepresented groups in computer science, finding differences in attitudes and resource utilization between students in the community and other programming students. Here we present the first statistically significant differences in pre- to post-quarter student attitudes between those in the learning community and others taking equivalent programming classes. We find that students in the learning community are less likely to feel isolated post-quarter than other programming students. Read More

With a plethora of available classification performance measures, choosing the right metric for the right task requires careful thought. However, analyzing measures with respect to complete ranges of their values is a difficult and challenging task. In this study, we attempt to support such analyses with a specialized visualization technique, which operates in a barycentric coordinate system using a 3D tetrahedron. Read More

This paper presents a two-dimensional phase extraction system using passive WiFi sensing to monitor three basic elderly care activities including breathing rate, essential tremor and falls. Specifically, a WiFi signal is acquired through two channels where the first channel is the reference one, whereas the other signal is acquired by a passive receiver after reflection from the human target. Using signal processing of cross-ambiguity function, various features in the signal are extracted. Read More

We present rootJS, an interface making it possible to seamlessly integrate ROOT 6 into applications written for Node.js, the JavaScript runtime platform increasingly commonly used to create high-performance Web applications. ROOT features can be called both directly from Node. Read More

This paper investigates the problem of implementing proportionate-type LMS family of algorithms in hardware for sparse adaptive filtering applications especially the network echo cancelation. We derive a re-formulated proportionate type algorithm through algorithm-architecture co-design methodology that can be pipelined and has an efficient architecture for hardware implementation. We study the convergence, steady-state and tracking performances of these re-formulated algorithms for white, color and speech inputs before implementing them in hardware. Read More

The number of events recorded for operational processes is growing every year. This applies to all domains: from health care and e-government to production and maintenance. Event data are a valuable source of information for organizations that need to meet requirements related to compliance, efficiency, and customer service. Read More

Spatiotemporal context is crucial in modern mobile applications that utilize increasing amounts of context to better predict events and user behaviors, requiring rich records of users' or devices' spatiotemporal histories. Maintaining these rich histories requires frequent sampling and indexed storage of spatiotemporal data that pushes the limits of resource-constrained mobile devices. Today's apps offload processing and storing contextual information, but this increases response time, often relies on the user's data connection, and runs the very real risk of revealing sensitive information. Read More

The rapid urbanization of developing countries coupled with explosion in construction of high rising buildings and the high power usage in them calls for conservation and efficient energy program. Such a program require monitoring of end-use appliances energy consumption in real-time. The worldwide recent adoption of smart-meter in smart-grid, has led to the rise of Non-Intrusive Load Monitoring (NILM); which enables estimation of appliance-specific power consumption from building's aggregate power consumption reading. Read More

We introduce a regression model for data on non-linear manifolds. The model describes the relation between a set of manifold valued observations, such as shapes of anatomical objects, and Euclidean explanatory variables. The approach is based on stochastic development of Euclidean diffusion processes to the manifold. Read More

The reliability of logical operations is indispensable for the reliable operation of computational systems. Since the down-sizing of micro-fabrication generates non-negligible noise in these systems, a new approach for designing noise-immune gates is required. In this paper, we demonstrate that noise-immune gates can be designed by combining Bayesian inference theory with the idea of computation over a noisy signal. Read More