Deregulation of power system has created competition in the power market shifting the focus from cost optimization to profit maximization, which has created different trading mechanisms. The power companies and their customers submit their bids for each trading interval of the next day and the independent system operator (ISO) conducts a bid based dynamic economic dispatch (BBDED) to allocate power to the generating companies and customers in such a manner that the total profit is maximized while all constraints such as power balance, operating limits and ramp rate limits are satisfied. Nature inspired (NI) optimization techniques score over the classical numerical methods for solving such complex practical problems due to (i) their population based random search mechanism and (ii) their non-dependence on initial solution. This paper proposes a symbiotic organisms search (SOS) based solution for solving BBDED problem in the deregulated electricity market. The SOS algorithm depicts the interaction between different species in nature, the three symbiotic relationships. The performance of the proposed approach has been tested on standard power system bench marks from literature having 10 generators, 6 customers and varying power demands over 12 dispatch periods. The results have been validated with published results and SOS is found to be more effective than the other methods for solving the BBDED problem.

According to the AQI data and the meteorological data of Xi’an in the last years, the relationships and the influence principles between PM2.5 and other five monitoring indicators of AQI, weather factors and heating time were analyzed, respectively, by the regression analysis and the ridge regression analysis. The main results include: (1) There were positive correlations between PM2.5 and SO2, NO2 and CO, which shows that SO2, NO2 and CO may be the major gaseous components of forming PM2.5. Therefore, the concentration of PM2.5 can be reduced by considering how to efficiently decrease the concentrations of SO2, NO2, and CO. (2) The relationships between PM2.5 and temperature, sea level press, visibility, wind speed and accumulated precipitation are significantly negatively correlated based on the multiple regression. (3) The concentration of PM2.5 during the heating period was 1.868 times higher than that during non-heating period. Finally, the ridge regression between PM2.5 and all the factors mentioned above shows that SO2, NO2, PM10, CO and heating time were more significant than others.

The synchronization of the Hindmarsh-Rose neuron system with external disturbance is investigated via sliding mode control. Based on the Lyapunov stability theory, a single sliding mode controller is derived even when the response Hindmarsh-Rose neuron system with external disturbance. The numerical simulation is presented to verify the effectiveness of the proposed control scheme.

Predicting protein-folding patterns is a challenge due to the complex structure of proteins. Many sequence encoding schemes have been proposed to extract the features of pro-tein sequences, and these features are often fused to form a new combined feature set so that it can contain various useful information. However, there usually has redundant information in the combined features. In this paper, a novel approach, LSDA-SVM, is proposed to predict pro-tein fold pattern. Firstly, protein samples are represented by the pseudo amino acid composition (PseAAC), pair wise feature (PF) and the others five types of protein sequence information, and these features are further combined to form a new feature set. Secondly, the locality sensitive discriminant analysis (LSDA) is employed to extract the more discriminant features. Finally, the support vector machine (SVM) is employed to classify the protein sequences. Experimental results demonstrate the effectiveness of the proposed algorithm.

Road Traffic Accident (RTA) cause serious threat to human life worldwide. Nigeria is not left out in this menace and in fact is ranked as one of the countries with a high number of RTA cases. This is alarming and a preventive measure is to be taken to avoid or reduce RTAs in the country. In this work, a system is developed to predict road accidents in Benue state using Artificial Neural Network (ANN) model. The road characteristics as well as environmental factors are used as parameters. Data of RTA from 2008 to 2014 was collected from the Federal Road safety Commission for predictions. The predictions will help policy makers as well as Federal Road Safety Commission to put in place measures to prevent occurrence of RTAs. The underlying database that store the RTA data was created using MYSQL relational database. The software was written using JAVA programming language and neuroph for the predictions.

In order to solve the problem that face recognition is sensitive to illumination variation and local binary pattern has small spatial support region. A novel face recognition approach which is multi-scale logarithmic difference face recognition based on local binary pattern is proposed. Firstly, LBP operator is used to extract the texture feature of the face. Secondly, the LBP feature is used to extract the light invariant based on the Lambertian reflection model. Then, the light invariant is used to obtain the multi-scale features according to the different distances, and the refined feature-map is obtained by the linear combination of multi-scale features. Finally, face recognition is performed using refined feature-map. Extension experiments on four data sets (Yale, FERET, ORL and MUI PIE) show that the proposed method which compares to LBP, MSLDE and Gradientface in different illumination conditions can improve the recognition performance.

In this paper, we have made an attempt to comparative study of the existing Haar wavelet collocation method with proposed new wavelet-Galerkin method for the solution of differential equations. The solutions obtained using proposed scheme are comparably good and give higher accuracy than existing ones with exact solution by increasing the level of resolution.To yield the solutions of differential equations using usal wavelet-Galerkin require use of connection coefficients, which takes large computational complexities and time consumption. The proposed scheme is rather simple and avoids the above complexities, which is demonstrated through the some of the test problems.

The paper discusses linear systems in imprecise environment. In this paper we have developed the solution procedure of system of linear equations with coefficients and the right-hand side as fuzzy and intuitionistic fuzzy numbers. We have also calculated the necessary and sufficient conditions for the existence of the solutions by developing some theorems. We have solved the system by using the concept of Strong and Weak solution with numerical example.

The goal of this paper is to solve a matrix game with fuzzy payoffs. In this paper, a fuzzy matrix game has been considered and its solution methodology has been proposed. In this paper, fuzzy payoff values are assumed to be trapezoidal fuzzy numbers. Then the corresponding matrix game has been converted into crisp game using defuzzification of fuzzy number. Here, widely known signed distance method has been used for defuzzification of fuzzy number. The value of the matrix game and strategy for each player is obtained by solving corresponding crisp game problems using the traditional method. Finally, a numerical example has been presented and solved.