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Fig 1.

Diagram of IRBF-FFA.

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Fig 2.

The architecture of the testbed.

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Fig 3.

Simulation scenario.

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Fig 4.

RBF Neural Network Structure.

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Fig 5.

Movement of colony toward its relevant imperialist.

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Fig 6.

Pseudo code for the Imperialist Competition Algorithm (ICA).

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Fig 7.

Description of the Firefly Algorithm (FFA).

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Fig 8.

Pseudo code for the IRBF-FFA.

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Fig 9.

Hybrid of ICA and RBF.

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Fig 10.

MLP network topology.

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Table 1.

Simulation parameters and channel characteristics.

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Fig 11.

The plots of IRBF–FFA model predicted versus actual values for training, testing and all data sets for N1, N2, N3, and N4.

(a) The RSSI prediction values for N1. (b) The RSSI prediction values for N2. (c) The RSSI prediction values for N3. (d) The RSSI prediction values for N4.

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Table 2.

Real and predicted RSSI values.

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Table 3.

The performances of IRBF–FFA model based on R2 and RMSE compares to other methodologies.

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Table 4.

The performances of IRBF–FFA model based on r and MAPE compares to other methodologies.

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Fig 12.

Comparing the number of vertical handoffs under various arrival rates.

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Fig 13.

Predicted RSSI of MT in three different networks (WiMAX & Wi-Fi& UMTS).

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