Cuckoo Cycle is a recently proposed “memory-hard” computational Proof-of-Work (PoW) function designed to require a minimum amount of memory to compute efficiently. This paper describes two algorithms that use the sparsity of the Cuckoo Cycle graph to use less memory than both the initially hypothesized and updated proposed bounds for this proof-of-work function. The second algorithm presents a ...

In this paper, an improved method based on evolutionary algorithm for speech signal denoising is proposed. In this approach, the stochastic global optimization techniques such as Artificial Bee Colony(ABC), Cuckoo Search (CS)algorithm, and Particle Swarm Optimization (PSO) technique are exploited for learning the parameters of adaptive filtering function required for optimum performance. It was...

Economic Load Dispatch problem (ELD) is one of the most important optimization problems in power system operation and planning. This paper introduces a solution to ELD problem using a new metaheuristic natureinspired algorithm called Cuckoo Search Algorithm (CSA). The proposed approach has been applied to various systems. This algorithm is based on the obligate brood parasitic behavior of some ...

Nature inspired meta-heuristic algorithms are iterative search processes which find near optimal solutions by efficiently performing exploration and exploitation of the solution space. Considering the solution space in a specified region, this work compares performances of Bat, Cuckoo search and Firefly algorithms for unconstrained optimization problems. Global optima are found using various te...

In this paper, a Cuckoo Search Algorithm (CSA) is proposed for solving environmental economic load dispatch (EELD) problem with quadratic fuel function. Cuckoo Search is a new meta-heuristic algorithm inspired from the obligate brood parasitism of some cuckoo species by laying their eggs in the nests of other host birds of other species for solving optimization problems with promising results. ...

To handle scheduling of tasks on heterogeneous systems, an algorithm is proposed to reduce execution time while allowing for maximum parallelization. The algorithm is based on multi-objective scheduling cuckoo optimization algorithm (MOSCOA). In this algorithm, each cuckoo represents a scheduling solution in which the ordering of tasks and processors allocated to them are considered. In additio...

Today, the information is growing enormously and it is difficult and tedious task to retrieve the necessary information from that pool. The main area for retrieving relevant answers is called intelligent information retrieval. To achieve this, question and answering system is used. This question and answering plays a major role in user query processing, information retrieval and extracting rela...

Cuckoo search (CS) is a novel biologically inspired algorithm and has been widely applied to many fields. Although some binary-coded CS variants are developed to solve 0-1 knapsack problems, the search accuracy and the convergence speed are still needed to further improve. According to the analysis of the shortcomings of the standard CS and the advantage of the global harmony search (GHS), a no...

Back-propagation Neural Network (BPNN) algorithm is one of the most widely used and a popular technique to optimize the feed forward neural network training. Traditional BP algorithm has some drawbacks, such as getting stuck easily in local minima and slow speed of convergence. Nature inspired meta-heuristic algorithms provide derivative-free solution to optimize complex problems. This paper pr...