Significance of Artificial Neural Network

Introduction to Artificial Neural Network

Artificial Neural Network (ANN) is a computing system, which is typically integrated in layers. These layers consist of complex reticulated elements which are known as neurons. Neurons are unified in the specific pattern inspired by the biological nervous system of brain. ANN has not programmed for a specific task but, it is used to solve more complex and complicated problems with the help of detection from observational data. Artificial neurons transmit signals to each other and addition of signals form a connection between neurons. The connections between neurons are called edges. The first layer receives information as input and after passing through the multiple layers approaches to the last layer known as output.

Introduction to Artificial Neural Network

Mechanism of Artificial Neuron Network

Before studying the mechanism of ANN it is imperative to learn the processing of human brain because, ANN is the reflection of human brain. In brain, neurons receive signal with the help of structure said as dendrites. Addition to this, neurons convey signal to synapse which is further connected with long-thin shaped structure known as axons. In ANN, the tendency of transmitting the signal to the next layer is dependent on the weight of artificial neurons and edges. Increase or decrease in weight effect the strength of signal at connection. Every neuron has threshold which works as barrier in the transmission of signal.

Advantages of Artificial Intelligence Neural Network

1- ANN has a peculiar property of generalizing the input which means that doesn’t matters what the input is but, neural network has ability to generalize its input and process it for conclusion.

2- Artificial neural network is the invention of modern age. If it is implemented in parallel architectures (i.e. in multi processers) then it will drastically reduce the time of processing of the system as compared to the other kind of algorithms or conventional computers. ANN has not able to process large amount of data sets only but it has ability to solve the complex, non-linear problems implicitly.

3- Artificial neural network is a non-parametric model that’s why this network doesn’t require a higher background of statistic. Back propagation with artificial neural network is widely used to solve forecasting problems now-a-days. Another property of this network is fault tolerance. This network has ability to route the node which is not communicating.

4- Artificial neural network is a diagnostic network because it has self debugging state. This is remarkable property of ANN. If it is asked to find out the data which is no longer communicating, then ANN has ability to regenerate the sets of data in order to quantify the inputs and conclude an output according to the available data.

Disadvantages Artificial Intelligence Neural Network

As we know everything has limitations, similarly artificial neural network also has some disadvantages which should be taken in to account in order to understand ANN.

1- This network may consists of hundreds or thousands number of elements depending on the size of system, so this property requires large amount of data for processing which is not easy to avail in specific situations.

2-Secondly, the conclusion of ANN is unpredictable. In case of wrong interpretation it may results blunder which lead towards the waste of time. This problem needs more knowledge and advancement in this field. The duration of process is also hard to guess because ANN can work with numerical information. Problems have to be translated into particular values before practicing in artificial intelligence neural network.

Conclusion

Artificial neural network is a subject with very vast knowledge. In this study, we only have discussed the introductory concepts. ANN is also working with very advanced techniques. There are numerous other precise rules other than back propagations. ANN has very intensive calculations so highly efficient computer machines are required for implementation. ANN has not yet explored completely, scientists are doing research on this. When research would be done, scholars believe that human beings would touch the new heights of exploration in the field of science and technology.

Tags: AI Neural Networks, ANN, Artificial Intelligence, Neural Networks

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