In this paper, detailed scalability and replicability plans have been developed to facilitate the adoption of innovation technologies in pan-EU market. Smart grid development must enable both information power exchange between suppliers customers, thanks enormous intelligent communication, monitoring, management systems. Implementing physical infrastructure alone is not enough, but a smart include new business models regulations. recent years, number, participants, scope initiatives...

The purpose of this study is to investigate the potential AI technology in developing a decision support system that can improve effectiveness wireless sensor networks (WSNs) e-commerce, specifically enhancing features consumer electronics. This research project focused on optimizing for e-commerce electronics by incorporating AI-based systems. primary objective enhance energy efficiency and performance online shopping platforms. Various algorithms methodologies are proposed assessed,...

Biological behaviors have inspired the development of numerous evolutionary optimization algorithms [...]

In coastal areas, coconuts are a common crop. Everyone from farmers to lawmakers and businesses would benefit an accurate forecast of coconut production. Internet Things (IoT) sensors strategically positioned continuously monitor the environment gather production statistics obtain agricultural output predictions. To effectively estimate prediction, this study presents enhanced deep learning classifier called Bi-directional Long Short-Term Memory (BILSTM) with integrated Lévy Flight Seagull...

Electric load forecasting is a process that has to be both fast and reliable.An accurate method of plays the most crucial role in achieving aforementioned properties also valuable tool overcoming variety economic operational problems connected electrical energy production distribution.In this study real data used performance three different techniques for adaptive electric evaluated.The first combination well-established multimodel partitioning filter (MMPF) implementing extended Kalman...

In this paper, a study on how to perform simultaneous order and parameter estimation of multivariate (MV) ARMA (autoregressive moving average) models under the presence noise is addressed. The proposed method, which computationally efficient, an extension previously presented method for MV AR based well established widely applied multi-model partitioning theory. A series computer simulations indicate that infallible in selecting correct model very few steps. parameters also another benefit...

In this study an adaptive algorithm for multivariate (MV) ARMA model order identification and parameter estimation is presented based on the multi-model partitioning theory (MMPT). The method proposed reformulation of problem in standard state space form implementing a bank Kalman filters, each fitting different model. first step will be to select MV using MPPT, general (not necessarily Gaussian) data pdf's. assumption made that true \theta (\lambda, \lambda) where \lambda = max (p, q), p AR...

Climate change and the increased level of power demand has led to a growing electrical energy production from renewable sources, such as wind power. The main problem associated with is nature speed which random non linear. This reason why forecasting difficult but crucial task, since its accuracy plays significant role in achieving reliable autonomous at same time contributes surpassing series problems, economic technical nature. In this study real data used performance three different...

This paper tackles the problem of long-term prediction electrical energy consumption with three different approaches using real data. The first method combines well-established multimodel partitioning filter (MMPF) implementing extended Kalman filters (EKF) Support Vector Machines (SVM), second is a hybrid MMPF and Genetic Algorithms (G.A) last implements an artificial multilayer layer feed-forward neural network (ANN). accuracy forecasting (considering time interval greater than one year)...

In this paper a microscopic, non-discrete, mathematical model based on stigmergy for predicting the nodal aggregation dynamics of decentralized, autonomous robotic swarms is proposed. The departs from conventional applications in bioinspired path-finding optimization, serving as dynamic algorithm nodes with limited or no ability to perform discrete logical operations, aiding agent miniaturization. Time-continuous simulations were developed and carried out where efficiency was evaluated using...

An alternative electric power source, such as wind power, has to be both reliable and autonomous. accurate speed forecasting method plays the key role in achieving aforementioned properties also is a valuable tool overcoming variety of economic technical problems connected production. The proposed based on reformulation problem standard state space form implementing bank Kalman filters (KF), each fitting an ARMA model different order. applied greenhouse unit which incorporates automatized...