Accurate wind power forecasting is essential to reduce the negative impact of on operation grid and cost system. Day-ahead plays an important role in day-ahead electricity spot trading market. However, instability series makes forecast difficult. To improve accuracy, a hybrid optimization algorithm established this study, which combines variational mode decomposition (VMD), maximum relevance &a...

We proposed a task scheduling in cloud computing based on intelligence firefly algorithm aimed at the disadvantages of cloud computing task scheduling. Firstly, on the basis of cloud model, used intelligence firefly algorithm with strong ability of global searching to find the better solution of cloud computing task scheduling then turned the better solution into the initial pheromone of improv...

This paper proposes adaptive neuro-fuzzy inference system (ANFIS) to predict the risk with its aggregated cost (CR) of an accident in road transportation hazardous material, aim is provide a more accurate and reliable data for safety transportation. The determination index by conventional methods such as Risk graphs deterministic approaches may lead imprecise values due uncertainties, both para...

Highly accurate interval forecasting of a stock price index is fundamental to successfully making a profit when making investment decisions, by providing a range of values rather than a point estimate. In this study, we investigate the possibility of forecasting an interval-valued stock price index series over short and long horizons using multi-output support vector regression (MSVR). Furtherm...

The performance of communication networks can be affected by a number of factors including misconfiguration, equipments outages, attacks originated from legitimate behavior or not, software errors, among many other causes. These factors may cause an unexpected change in the traffic behavior and create what we call anomalies that may represent a loss of performance or breach of network security....

Nature-inspired algorithms such as Particle Swarm Optimization and Firefly Algorithm are among the most powerful algorithms for optimization. In this paper, we intend to formulate a new metaheuristic algorithm by combining Lévy flights with the search strategy via the Firefly Algorithm. Numerical studies and results suggest that the proposed Lévy-flight firefly algorithm is superior to existing...

6 Highly accurate interval forecasting of a stock price index is fundamental to 7 successfully making a profit when making investment decisions, by providing a range 8 of values rather than a point estimate. In this study, we investigate the possibility of 9 forecasting an interval-valued stock price index series over short and long horizons 10 using multi-output support vector regression (MSVR...

The growing costs of fuel and operation of power generating units warrant improvement of optimization methodologies for economic dispatch (ED) problems. The practical ED problems have non-convex objective functions with equality and inequality constraints that make it much harder to find the global optimum using any mathematical algorithms. Modern optimization algorithms are often meta-heuristi...

Firefly algorithm is a swarm-based algorithm that can be used for solving optimization problems. In this paper, we focus on image clustering algorithm using the fuzzy set of possible solution is incorporated into the original firefly to improve the performance. The movement of the firefly still follows the original pattern but they are updated according fuzzy c-means algorithm. All method, k-me...

Annual crop planning (ACP) is an NP-Hard type optimisation problem in agricultural planning. It involves finding optimal solutions for the seasonal allocations of a limited amount of agricultural land among the various competing crops that need to be grown on it. This study investigates the effectiveness of employing three relatively new Swarm Intelligence (SI) techniques in determining solutio...