| ABSTRACT | 第1-9页 |
| 摘要 | 第9-11页 |
| LIST OF ABBREVIATIONS | 第11-21页 |
| ACKNOWLEGEMENT | 第21-23页 |
| CHAPTER 1 INTRODUCTION | 第23-45页 |
| ·Background of complex adaptive system | 第23-35页 |
| ·Neural network learning | 第27-29页 |
| ·Scale free network | 第29-30页 |
| ·Small world network | 第30-32页 |
| ·Underground mining and wireless sensor networks examined | 第32-35页 |
| ·Routing in wireless sensor networks,signal reach and sensor deployment | 第35页 |
| ·The concept and design | 第35-42页 |
| ·Objective | 第38-39页 |
| ·Significance | 第39-40页 |
| ·Proposed model | 第40-42页 |
| ·Procedure for generation of the model | 第42-44页 |
| ·Generation of the routing path | 第42页 |
| ·Operation of particle swarm optimization | 第42-43页 |
| ·Operation of genetic algorithm | 第43-44页 |
| ·Main Works and Novelty | 第44-45页 |
| CHAPTER 2 LITERATURE REVIEW | 第45-55页 |
| ·Introduction | 第45-46页 |
| ·Sigmoid basis function | 第46-48页 |
| ·Radial basis function neural network | 第48页 |
| ·Hybrid Models or algorithms | 第48-52页 |
| ·Method | 第52-55页 |
| ·Particle swarm optimization(PSO) | 第52-53页 |
| ·Genetic algorithm | 第53-55页 |
| CHAPTER 3 ROUTING TOPOLOGY,NEW COMPACT RADIAL AND SIGMOID NEURALNETWORKS | 第55-83页 |
| ·Introduction | 第55页 |
| ·Related work | 第55-56页 |
| ·Proposed routing topology | 第56-65页 |
| ·Deployment of sensors and connection | 第56-58页 |
| ·Communication and transmission range | 第58-62页 |
| ·Fault tolerant considerations | 第62-64页 |
| ·Hardware and software considerations | 第64-65页 |
| ·Simulation results and discussion | 第65-68页 |
| ·Sensor sequence and routing | 第65-66页 |
| ·Impact of explosion on transmission | 第66-67页 |
| ·Re-routing | 第67-68页 |
| ·The new compact radial and sigmoid neural networks | 第68-74页 |
| ·Introduction | 第68-69页 |
| ·Gaussian RBF | 第69-70页 |
| ·Gaussian with different power parameter | 第70页 |
| ·Proposed compact radial basis function (CRBF) | 第70-72页 |
| ·Evaluation of the fitness function | 第72-74页 |
| ·Simulation parameters, results and discussion | 第74-82页 |
| ·Parameters for simulation | 第74-75页 |
| ·Results and discussion | 第75-82页 |
| ·Conclusion | 第82-83页 |
| CHAPTER 4 WEIGHTED LINEAR AND NONLINEAR HYBRIDS NEURAL NETWORKS IN UNDERGROUND RESCUE MISSION | 第83-126页 |
| ·Introduction | 第83页 |
| ·Related work | 第83-85页 |
| ·The proposed weighted linear hybrid of sigmoid and compact radial functions | 第85-99页 |
| ·Simulation results and discussion | 第86-99页 |
| ·Weighted nonlinear hybrid neural networks of compact sigmoid and radial functions | 第99-109页 |
| ·Proposed nonlinear hybrid | 第99-100页 |
| ·Results and discussion | 第100-109页 |
| ·G-ratio weighted nonlinear hybrid neural networks | 第109-124页 |
| ·Simulation results and Discussion | 第112-124页 |
| ·Conclusion | 第124-126页 |
| CHAPTER 5 NEW COMPACT RADIAL BASIS FUNCTION WITH GENETIC ALGORITHM | 第126-149页 |
| ·Introduction | 第126页 |
| ·Related work | 第126-129页 |
| ·Limitations | 第128-129页 |
| ·Proposed Compact hybrid model based on Genetic Algorithm | 第129-133页 |
| ·Simulation results and discussion | 第133-147页 |
| ·The generated matrices | 第133-135页 |
| ·Training results | 第135-141页 |
| ·Performance of parameters of the various hybrids | 第141-144页 |
| ·General performance and computational efficiency | 第144-147页 |
| ·Conclusion | 第147-149页 |
| CHAPTER 6 CONCLUSION AND FUTURE WORK | 第149-152页 |
| REFERENCES | 第152-163页 |
| LIST OF PUBLICATION | 第163页 |
