What is artificial neural network in soft computing?
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20 Citations | Among these, the artificial neural network (NN) system appears to be a powerful tool to tackle situations in w... |
Open access 01 Jan 2005 44 Citations | Artificial neural network, a biologically inspired computing method which has an ability to learn, self-adjust, and be trained, provides a powerful tool in solving pattern recognition problems. |
| Artificial neural network is a versatile modelling tool capable of making predictions of values that are difficult to obtain in numerical analysis. | |
11 Jul 2018 12 Citations | Artificial neural networks (ANN) are the valuable and attractive soft computing method for prediction. |
| An artificial neural network, a biologically inspired computing method which has an ability to learn, self-adjust, and be trained, provides a powerful tool in solving complex problems. | |
08 May 1989 26 Citations | One popular artificial neural network model, the back-propagation algorithm, promises to be a powerful and flexible learning model. |
| Artificial neural networks (ANNs) are a particularly promising branch on the tree of soft computing, as they possess the ability to determine nonlinear relationships and are particularly adept at dealing with noisy data sets. | |
| Artificial Neural Network, which is a soft computing technique, is a constructive advance towards building an intuitive system which will be suited for processing the nonlinear conditions of weather and make prognosis. | |
20 Citations | The artificial neural network provides an advanced computing model, which allows more factors to be involved. |
13 Citations | Soft Computing techniques based on artificial neural networks may be a way to implement more efficient control strategies in order to obtain a suitable power demand each and every time. |
Related Questions
What is an artificial neural network?4 answersAn Artificial Neural Network (ANN) is an information processing paradigm inspired by biological nervous systems, like the brain, designed to solve problems by mimicking the behavior of neurons and synapses. ANNs consist of interconnected processing elements (neurons) that learn from examples, similar to humans, through a training process for specific applications such as pattern recognition or data classification. These networks aim to implement a simplified model of the human brain, where neurons communicate with each other through synapses to process information and learn tasks. ANNs play a crucial role in machine learning, supporting supervised learning, unsupervised learning, and reinforcement learning, with the backpropagation algorithm being a key training method for neural networks.
What is Artificial neural networks?4 answersArtificial Neural Networks (ANNs) are computational models inspired by the human brain's information processing system. ANNs consist of interconnected processing elements called neurons, which work together to solve problems. Similar to the brain, ANNs learn from examples and adjust their synaptic connections to improve performance. ANNs have various applications, including pattern recognition and data classification. They aim to mimic the behavior of the brain by implementing simplified models of neurons and their interconnections. ANNs can receive stimuli, emit signals, and communicate with other neurons, enabling learning and problem-solving. ANNs are a type of machine learning that uses the brain's processing as a basis for developing algorithms to model complex patterns and prediction problems. They are also a part of deep learning, which processes data in complex patterns and automates tasks that require human-like intelligence.
What is Artificial Neural Network?5 answersAn Artificial Neural Network (ANN) is a computational model inspired by the structure and functioning of the human brain. It consists of interconnected processing elements called neurons that work together to solve specific problems. ANNs learn from examples and are trained for specific applications such as pattern recognition and data classification. The learning process in ANNs involves changing the synaptic connections between neurons. ANNs aim to mimic the behavior of the brain by implementing a simplified model of its functioning. They are a type of computational method belonging to the field of Machine Learning. ANNs have evolved since their inception in the 1980s, with advancements such as the backpropagation algorithm and the emergence of convolutional neural networks and deep learning.
What is artificial neural network?5 answersAn Artificial Neural Network (ANN) is a computational model inspired by the structure and function of the human brain. It consists of interconnected processing elements called neurons, which work together to solve specific problems. ANNs learn from examples and can be trained for tasks such as pattern recognition and data classification. The learning process involves adjusting the synaptic connections between neurons, similar to how learning occurs in biological systems. ANNs aim to mimic the behavior of the brain by implementing a simplified model of its neurons and their interconnections. They have become a key component of machine learning and artificial intelligence, with applications in various fields. The backpropagation algorithm is a commonly used learning algorithm for ANNs. Overall, ANNs provide a powerful tool for processing and analyzing data, with the potential to bridge the gap between computer and human intelligence.
What is artificial neuro network?5 answersAn Artificial Neural Network (ANN) is an information processing paradigm inspired by the way biological nervous systems, such as the brain, process information. It consists of interconnected processing elements called neurons that work together to solve specific problems. ANNs learn from examples and can be trained for tasks like pattern recognition and data classification. The structure of ANNs is designed to mimic the behavior of the human brain, with neurons communicating through connections called synapses. The power of ANNs lies in their ability to process information in parallel and learn from large datasets. They have applications in modeling complex patterns, prediction problems, and intelligent control systems. Deep learning, a type of ANN, processes data in complex patterns and can automate tasks that require human brain-like processing.
What is the artificial neural networks?5 answersArtificial neural networks (ANNs) are computational methods that aim to implement a simplified model of the human brain. ANNs learn tasks by mimicking the behavior of the brain, which is composed of interconnected neurons. Neurons receive stimuli and emit signals, allowing them to communicate with each other. ANNs can be trained to approximate any computable function and have been used in various fields such as computer vision, robotics, speech recognition, and natural language processing. The historical evolution of ANNs includes the development of learning methods, such as the backpropagation algorithm, and recent advances in convolutional neural networks and deep learning. Neural networks learn through training or learning processes, where input and output associations are formed and adjusted to achieve accurate results. They have proven to be effective in applications such as system identification and control, face recognition, and solving nonlinear phenomena.