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On the side of enhancing the execution of skills, specialists in sports are adopting analysis of kinematics to correct actions of an athlete. By means of technological resources used to measure physical variables and to supply relevant data to trainers, results related to improvements on athletes' performance are being achieved. In this context, this work uses the Radial Basis Function Neural Networks...
Rainfall is a vital phenomenon that contributes in the success of sugar industry season. The ability to determine the amount of precipitation in sugarcane areas enhances the profitability of the season. Different types of climate indices and attributes are usually applied to model rainfall forecasting systems. In this paper, we present a novel genetic algorithm based feature selection approach to...
As scientific applications become more data intensive, finding an efficient scheduling strategy for massive computing on network-based computing systems has drawn increasingly attention. Most existing scheduling models assume that all processors are idle at the beginning of workload assignment. In fact, in the real distributed computing environments, processors may still be occupied with any previous...
Seedling emergence is one of the most important phenological processes that influence the success of weed species. Therefore, predicting weed emergence timing plays a critical role in scheduling weed management measures. Important efforts have been made in the attempt to develop models to predict seedling emergence patterns for weed species under field conditions. Empirical emergence models have been...
Electrical discharge abrasive grinding (EDAG) of ferrous alloys such as high speed steel and high carbon steel, using diamond abrasive demonstrates poor machining performance. The chemical affinity of diamond towards the ferrous alloys is the main reason for the same. In the present research, the performance of cubic boron nitride (CBN) abrasive has been investigated. The parametric analysis, modeling...
Investments on smarter solutions for power systems are currently growing and many large Smart Grid projects are underway throughout the world. With photovoltaic and wind power generation, consumers will also be able to produce and sell energy. This distributed generation will require a very efficient management of the power system. In this context, smart meters will be crucial tools to measure and...
Currently, low power Metal Oxide gas Sensors (MOXs) are widely employed in gas detection because of its benefits, such as high sensitivity and low cost. However, MOX presents several problems, as well as lack of selectivity and environment effect. In this paper, it is presented an Artificial Neural Network (ANN) that models an MOX sensor (TGS 2610) used in a operating environment. The structure and...
Snake robots are redundant structures, that are able to traverse many unstructured environments unlike wheeled and legged mobile robots. This research presents a novel method of designing efficient movement control systems for snake robots using artificial neural networks, optimized by a genetic algorithm. This approach outperforms the common control methods in terms of diversity, using no a-priori...
Non linear time series modeling and forecasting has fundamental importance to various practical domains and a lot of active research work is going on in this area during past several years. In this work, an artificial neural network based model is used for load forecasting. Further, its performance is improved by using a canonical genetic algorithm. The method is supported by giving the forecasting...
A smart city is emerging as an application of information and communication technologies to mitigate the problems generated by the urban population growth. One of the smart city solutions is to establish an efficient fleet management relating to the use of a fleet of vehicles (e.g., ambulances and police vehicles). The most basic function in a fleet management system is the real time vehicle tracking...
An imbalanced or inappropriate dataset can have a negative influence in classification model training. In this paper we present an evolutionary method that effectively weights or samples the tuples from the training dataset and tries to minimize the negative effects from innaprotirate datasets. The genetic algorithm with genotype of real numbers is used to evolve the weights or occurrence number for...
Due to the fact that the smallest principal field stress from pumping pressure graphs in leak-off tests (LOTs) by using traditional theory is always greater than the real values, this paper introduce a new method to improve estimation of the smallest principal field stress of a subsurface strata based on the information provided in LOTs, and the maximum horizontal in-situ stress is also improved....
In this paper two computational intelligence methods are considered. In the first one the Neural Network based Controller with combination of Genetic Algorithm network structure optimization is presented. In the second example fuzzy logic control system is developed and implemented on industrial heating plant. Obtained knowledge considered as a part of the modular ICS (Intelligent Control System)...
Breast cancer is the development of a malignant tumor notably in the breasts of a female. No proven cure is yet known for breast cancer, except when detected at an initial stage. This paper presents an innovative approach to the diagnosis of breast cancer by using two proposed variants of Genetic Algorithms, the Inter-Genetic Algorithm, and the Intra-Genetic Algorithm, that evolves an ensemble of...
In the business sector, it has always been a difficult task to predict the exact daily price of the stock market index, hence, there is a great deal of research being conducted regarding the prediction of the direction of stock price index movement. Many factors such as political events, general economic conditions, and traders' expectations may have an influence on the stock market index. There are...
Advanced Driving Assitance Systems (ADAS) cover a wide range of systems that aim to provide increasingly a safe and efficient driving. Many of these systems are endowed with some intelligent skills which are, in many cases, addressed by means of Soft Computing (SC) paradigms like Neural Networks (NN) or fuzzy systems among others. However, SC algorithms require normally large computational resources...
Following analyzing existing challenges in addressing the balance between exploration and exploitation encountered by evolutionary algorithms, this paper develops a Genetic Algorithm with speciation (GASP). It first incorporates a novel encoding scheme and recombination method for a balanced genetic divergence when locating global optima in complex applications, such as structural and dynamic design...
This paper presents the implementation of an artificial intelligence strategy genetic algorithm (GA) in the photovoltaic (PV) connected cascaded h-bridge multilevel inverter (CHB-MLI). In the presence of the worst maximum power point (MPP) due to temperature or irradiance mismatches, a voltage imbalance condition occurs in the PV systems. Here, genetic algorithm is used to find the most optimized...
Machine control using electroencephalography (EEG) based brain computer interfaces (BCI) has been extensively researched in the past decade. However, research is often based on event bound methods such as motor imagery. Despite being useful in medical applications, even bound methods limit users' operational capability while performing BCI control. To alleviate the said limitation, we explore a robot...
Most of the existing methods for dam behavior modeling presuppose temporal immutability of the modeled structure and require a persistent set of input parameters. In real-world applications, permanent structural changes and failures of measuring equipment can lead to a situation in which a selected model becomes unusable. Hence, the development of a system capable to automatically generate the most...
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