Contribution of Tipu Sultan to rocket technology

The objective of this chapter is to highlight the contribution of Sultan Fateh Ali Tipu (1750-1799 A.D), the Sultan ofMysore, who was the pioneer of iron-cased rocket artillery technology. Tipu ruled Mysore for 17 years (l782-1799).The history of rockets or 'fireerrors' invention started from 1232 by Chinese and then followed by Europeans in the 14th and 15th centuries. Rocket bodies in this period were built using light materials such as bamboo, wood or paper since these materials can be easily obtained. However, towards the beginning of 16th century, the military scientists put more concentration to the development of canon. Thus, rockets was neglected due to invention and large improvement of canon. In the 18th century, rocket application reemerged during the Mysore time under the rule of Hyder Ali, (Tipu's father) and Tipu with totally improved version which was more superior than canon and existing rockets in China and Europe. The reemergence of the rockets created significant history in Indo-British technolog

Contribution of Lofti Asker Zadeh to fuzzy logic

The objective of this chapter is to highlight the contribution of Lofti Asker Zadeh, the founder of fuzzy logic. Lotfi Zadeh introduced the concept of fuzzy logic through his published paper 'Fuzzy sets' in 1965. The literal meaning of fuzzy is vague, imprecise, subjective or uncertain which gives impression that fuzzy logic is the 'logic' that is fuzzy. However, that assumption is misleading since the actual meaning of fuzzy logic is the logic used to describe fuzziness or imprecise thing (Negnevitsky, 2002, p. 87). Fuzzy logic allows machine to imitate the human thought process, while solving uncertainty problems by means of 'computing with the words' technique. In this technique, all the words by given each of linguistic variables have different degree of membership values (base on human perception) in the fuzzy set. This idea is similar to human decision making technique since used to judge something with linguistic variable such as 'good', 'better' , 'nice' which are uncertain and very subjective because it based on individual perception of something which and thus may differ from one person to another. Fuzzy set theory led to development of various intelligent machines that able to decide the solution in the way more to 'human like manner' which called Intelligent System (IS) to deal with uncertainty and impreciseness of real world problems

Application of intelligent technique for development of Colpitts oscillator

In this paper, new method of Colpitts oscillator designing through combination of Genetic Algorithm and Artificial Neural Network (ANN) has been suggested. The Thevenin's resistors for the common base Colpitts oscillator are optimized through application of GA and ANN. The developed common base Colpitts oscillator has shortest transient time response and stable Direct Current (DC) stability in the long term operation. Involvement of GA and ANN successfully optimize between transient time response and steady state response of common base oscillator. Application of these two artificial intelligent techniques assist faster selection of optimizes components values such as resistance values during circuit development rather than conventional method which used intuition techniques to develop the circuit

A Review of Forecasting Techniques

This work examines recent publications in forecasting in various fields, these include: wind power forecasting; electricity load forecasting; crude oil price forecasting; gold price forecasting energy price forecasting etc. In this review, categorization of the processes involve in forecasting are divided into four major steps namely: input features selection; data pre-processing; forecast model development and performance evaluation. The various methods involve are discussed in order to provide the overall view about possible options for development of forecasting system. It is intended that the classification of the steps into small categories with definitions of terms and discussion of evolving techniques will provide guidance for future forecasting sytem designers

A hybrid technique for dinar coin price prediction using artificial neural network based autogressive modeling technique

The recent introduction of Islamic Gold (Dinar) and Silver (Dirham) coins around the world has brought about a new paradigm in the world financial, economic and monetary system. The importance of accurately predicting the price of these coins ahead of time will contribute significantly to its usage for: daily transaction, investment and development of necessary infrastructures for the universal adoption of these coins. Thus in this work, recently proposed artificial neural network based autoregressive (ANN-BASED AR) modeling technique has been applied in predicting accurately the daily price of Islamic Dinar coin. The input data is formatted to meet the input data requirement of the ANN-based AR model. The formatted data are then fed to the ANN-based AR model for parameters estimation. Upon convergence, the required model coefficients are computed from the synaptic weights and adaptive coefficients of the activated function in a two layer feed forward back-propagation artificial neural network (ANN) system. Performance analysis of the proposed approach shows that this proposed hybrid technique can accurately predict the price of Dinar coin and the use of this approach shows better performance when compared to the use of linear prediction technique. Other likely areas of application of the proposed approach have also been presented in this paper

A novel hybrid artificial intelligence technique for colpitts oscillator design

In the design of the common base Colpitts oscillator, the resistance values of Thevenin’s resistors significantly influenced the transient time and steady state response of the resulting circuit. Various traditional approaches such as intuitive reasoning, mathematical calculation, and simulation-based techniques have been proposed in the literature for this purpose. Some of the aforementioned techniques involve rigorous mathematics, intuition, and experimentation in determining appropriate component values for optimal performance, stable steady state performance, and short transient response time from the resulting oscillator. In this paper, a new method of designing Colpitts oscillator using hybrid artificial intelligence comprising evolutionary-based Genetic Algorithm (GA) and artificial neural network (ANN) has been proposed. GA has been used in selecting various optimum resistance values of Thevenin’s resistors for maximizing long-term stability of the outputwaveform thus ensuring stable steady response of the designed circuit. ANN has been utilized in learning the nonlinear relationship between Thevenin’s resistors and transient time response of the Colpitts oscillator. Upon ANN convergence, optimum resistance values of obtained from GA process are fed into the trained ANN in predicting transient response time of each circuit. Optimized values with the shortest transient response time are finally selected for the Colpitts oscillator. The designed circuit successfully achieved optimization between its transient time response and steady state response. Hence, successfully reducing computation associated with existing traditional techniques in designing similar optimum Colpitts oscillator and achieving stable steady state output. Furthermore, this work has also demonstrated that ANN is capable of predicting the transient time of circuit with reasonable accuracy