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In this paper, a novel population-based metaheuristic optimization algorithm, which is named as Simulated Kalman Filter (SKF), is introduced for global optimization problem. This new algorithm is inspired by the estimation capability of the well-known Kalman Filter. In principle, state estimation problem is regarded as an optimization problem and each agent in SKF acts as a Kalman Filter. An agent in the population finds solution to optimization problem using a standard Kalman Filter framework, which includes a simulated measurement process and a bestso- far solution as a reference. To evaluate the performance of the SKF algorithm, it is applied to 30 benchmark functions of CEC 2014 for real-parameter single-objective optimization problems. Statistical analysis is then carried out to rank SKF results to those obtained by other metaheuristic algorithms. The experimental results show that the proposed SKF algorithm is a promising approach and able to outperform some well-known metaheuristic algorithms, such as Genetic Algorithm, Particle Swarm Optimization, Black Hole Algorithm, and Grey Wolf Optimizer.

Pensyarah FKEE UMP Kongsi Kepakaran Dalam Pengaturcaraan dan Pembinaan Lego Mindstrom

Pekan 23 Februari - Fakulti Kejuruteraan Elektrik dan Elektronik (FKEE) Universiti Malaysia Pahang (UMP) dengan kerjasama Pejabat Pendidikan Daerah Pekan (PPD) menganjurkan Bengkel Traning of Trainers (TOT), Pekan baru-baru ini.

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Innovate 2017 - the STEM EcoSystem

UMP Pekan 14 July - As the Pahang State Level host for this year’s championship, we welcome you to the 2017 Young Innovate Malaysia Competition. YI 2017 provides a highly competitive platform for academicians, teachers, industries and most importantly the future generation - our school children.

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On 17th May 2017, 20 of the faculty staffs were involved in “Santai Sains Bersama FKEE”: a STEM outreach program at Sek. Keb. Sri Maulana in Pekan, Pahang. This is.

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Program GTEX ENHANCING GRADUATE SKILLS TOWARDS EMPLOYABILITY ini merupakan program persedian kepada pelajar universiti tahun akhir yang bakal melalui alam pekerjaan.

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