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Although there are widely used methods as Genetic Algorithms, Fuzzy Logic and Artificial Neural Network, the Optimization Based Tools are considered the future of the systems of information. This issue is about Artificial Neural Network (ANN) used in Short Term Load Forecast (STLF). It proposes that the method is valid to predict STLF and how important it is on demand scheduling, contingency analysis,...
Repetitive respiratory disturbance during sleep is called Sleep Apnea Hypopnea Syndrome and causes various diseases. Different features and classifiers have been used by different researchers to detect sleep apnea. This study is undertaken to identify the better performing blood oxygen saturation features subset using an Artificial Neural Network classifier for sleep Apnea detection. A database of...
Security/Safety is managed, mostly, by means of integrated systems which have to consider, more and more, sensors, devices, cameras, mobile terminals, wearable devices, etc. that use wireless networks, to ensure protection of people and/or tangible/intangible assets from voluntary attacks, allowing also the safe management of the related consequent emergency situations that can derive from the above...
This paper presents a deep analysis of literature on the problems of optimization of parameters and structure of the neural networks and the basic disadvantages that are present in the observed algorithms and methods. As a result, there is suggested a new algorithm for neural network structure optimization, which is free of the major shortcomings of other algorithms. The paper describes a detailed...
Solvents are used in a large number of industries especially in cleaning and cosmetic. Solvents are known to be harmful to human health. Classification of solvent in a product is important to determine the level of hazard that can people faced. In this study, three different solvents, methanol, acetone, and chloroform, are used to obtain binary gas mixtures in a laboratory environment. A gas sensor...
Reconfigurable manufacturing systems are susceptible to disturbances because of the characteristics associated with changeover of machine configuration and functionality. An Artificial Neural Network Driven Decision-Making System can mitigate these disturbances, if applied with extensive knowledge of the manufacturing system. This paper introduces a new concept into the paradigm of agile manufacturing...
Web services evolve over time to fix bugs or update and add new features. However, the design of the Web service's interface may become more complex when aggregating many unrelated operations in terms of context and functionalities. A possible solution is to refactor the Web services interface into different modules that help the user quickly identifying relevant operations. The most challenging issue...
This paper presents the self-tuning PID parameters by applying Artificial intelligence(AI) algorithm for tuning the Brush DC motor. This proposed approach combines with two algorithms, so called the NN-GA, which are the Neural Network (NN) and the Genetic algorithm(GA). To show the effectiveness of the designed approach, the simulation results are then given. In addition, the simulation results are...
VANETs are network of vehicle which is formed dynamically for short duration. Due to this they are susceptible to various types of attacks. This paper discusses the recent techniques used to counter various types of attacks that threaten the VANET. Researchers have proposed many solutions to solve these problems. This paper discusses all the most relevant solutions and analyzed them according to various...
Level control is one of the most used processes in industries. However, it can present nonlinearities, which can make difficult its project. The PID controller is still a commonly used topology due to the non-necessity to know the full system dynamics, only the modelling that well describes the system behavior. The objective of this work is to identify, control and audit a level tank system from a...
In this paper, a proportional-integral-derivative (PID) controller integrated with a neural network (NN) is proposed to ensure quality of service (QoS) bandwidth requirements in passive optical networks (PONs). To the best of our knowledge, this is the first time an approach that implements aNNto tune a PID to dealwithQoS in PONs is used. In contrast to other tuning techniques such as Ziegler– Nichols...
Pixel classification in land scape images has been found to be challenging. The problem becomes more challenging in forest images due to the similar spectral features of pixels situated close to each other. Geographically weighted variables have been employed to classify the two different species namely Cryptomeria japonica (Japanese Cedar or Sugi) and Chamaecyparisobtusa (Japanese Cypress or Hinoki)...
Electrical load forecasting is essential in the field of power systems to enhance the operation and economical utilization In this paper, a combined approaches of artificial neural networks (ANN) with particle-swarm-optimization (PSO) and genetic algorithm optimization (GA) for short and mid-term load forecasting is developed. The model identifies the relationship among load, temperature and humidity...
Power generation from wind generators is always associated with some intermittency due to wind speed and other weather parameters variation, and accurate short-term forecasts are essential for their efficient and effective operation. This can well support transmission and distribution system operators and schedulers to enhance the power network control and management in the smart grid context. This...
The paper presents a real-time algorithm to compute the switching angles to control a three-phase multilevel cascaded inverter in order to minimize the THD to improve the EMC of the system. In particular, the proposed method uses an Artificial Neural network, trained by the GA algorithm, to identify the optimal switching angles corresponding to several values of DC sources voltage levels and the modulation...
The purpose of this paper is to understand various problems related to Computer Science and find solutions from optimized machine learning algorithm by realizing machine learning API and API server. The representative machine-learning algorithm, TensorFlow, need to express algorithm from the stage of nodes and edges while IBM Watson only uses functions in completed form. Those are the problems to...
Artificial Neural Network (ANN) is a widely used technique in forecasting applications. An ensemble of ANNs can produce more accurate forecasts than a single ANN. The performance of the ensemble depends on its' member ANN. Member selection for an ensemble is a complicated task that need balancing conflicting conditions. This paper presents a method to optimize the selection of members for an ANN ensemble...
We present a novel method for training (evolving) fully convolutional neural networks (CNNs) for deformable object manipulation. Instead of using a weight update rule, we evolve an ensemble of compositional pattern generating networks (CPPNs) by means of a genetic algorithm (GA). These ensembles generate the convolutional kernels that comprise the CNN. This allows the GA to search for fit kernels...
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...
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