most citedNew Hoopoe Heuristic Optimization

9 citations · 18 across the 7 of their papers we have counts for

collaborators

7 papers

cs.NE20123 cited

Collaborating Robotics Using Nature-Inspired Meta-Heuristics

M. A. El-Dosuky, M. Z. Rashad, T. T. Hamza +1

This paper introduces collaborating robots which provide the possibility of enhanced task performance, high reliability and decreased. Collaborating-bots are a collection of mobile…

cs.NI2012

New SpiroPlanck Heuristics for High Energy Physics Networking and Future Internet Testbeds

M. A. El-Dosuky, M. Z. Rashad, T. T. Hamza +1

The need for data intensive Grids, and advanced networks with high performance that support our science has made the High Energy Physics community a leading and a key co-developer…

cs.AI2012

Improving problem solving by exploiting the concept of symmetry

M. A. El-Dosuky, M. Z. Rashad, T. T. Hamza +1

We investigate the concept of symmetry and its role in problem solving. This paper first defines precisely the elements that constitute a "problem" and its "solution," and gives se…

cs.NE2012

Spike and Tyke, the Quantized Neuron Model

M. A. El-Dosuky, M. Z. Rashad, T. T. Hamza +1

Modeling spike firing assumes that spiking statistics are Poisson, but real data violates this assumption. To capture non-Poissonian features, in order to fix the inevitable inhere…

cs.NE20129 cited

New Hoopoe Heuristic Optimization

Mohammed El-Dosuky, Ahmed EL-Bassiouny, Taher Hamza +1

Most optimization problems in real life applications are often highly nonlinear. Local optimization algorithms do not give the desired performance. So, only global optimization alg…

cs.RO20121 cited

Simulated Tom Thumb, the Rule Of Thumb for Autonomous Robots

M. A. El-Dosuky, M. Z. Rashad, T. T. Hamza +1

For a mobile robot to be truly autonomous, it must solve the simultaneous localization and mapping (SLAM) problem. We develop a new metaheuristic algorithm called Simulated Tom Thu…