## 4 Experiments and Results
On the simulation platform, the performance metrics such as link quality prediction rate, system precision rate, average routing delay, and secure throughput rate are measured for the proposed model and the existing models (SMC, CRLR, and OETN). In addition, the reactive link establishment rate and retransmission reduction rate are considered as crucial factors for ensuring the stability and efficiency of proposed DMCAP model against exiting techniques. \[\text{Reactive Retransmission Rate}=\frac{\text{DMNR\_t}}{\text{UTt}}*100 \tag{30}\]  
* \(\text{DMNR\_t}\)Number of Retransmission taken at one iteration by DMCAP;
* \(\text{UTt}\)Number of network or link failures happens at one iteration. \[\text{Retransmission Reduction Rate}=\frac{\text{DMNR\_t}}{\text{ NRTt}}*100 \tag{31}\]  
* \(\text{NRTt}\)Total number of retransmissions taken without proposed DMCAP. Equations (30) and (31) illustrate the importance of the growth shown in Tables 5 and 6 for the proposed DMCAP model. As discussed, the proposed model uses more unique multi-channel modelling schemes for differentiating the characteristics of each wireless channel (air medium or acoustic medium). In addition, the combination of channel distortion analysis and malicious turbulences over the channel are taken seriously to predict the link stability to initiate multi-path transmission in WUGSN. The detailed channel analysis and attribute assessment schemes improve the data throughput over uncertain channels. Consequently, Table 7 illustrates the energy optimization rate achieved through the reduction in retransmission rate. Furthermore, this article found the coverage problems during wireless communication in the WUGSN and near ground sensor networks. Likewise, a few notable works are considered under this technical scope [50; 51]. As the uncertain channel qualities and coverage irregularities create crucial network problems, these are expected to be considered as major parts under any research cases [52]. medium and air medium to lead multi-hop wireless links. According to the link nature, the channel configuration parameters change from one link to another link in the same channel. Correspondingly, the impact of underground channel distortions and surface channel distortions create major problems for WUGSN communication. The channel is disturbed due to underground noise, interference, and malicious interactions. The rate of channel interruptions is not common for surface transmission with widely varying uncertainty rates [53; 54; 55]. Against the significant problems, the proposed DMCAP model was developed as a distributed sensor agent. The DMCAP model contained multi-channel signaling models, EMLP, ENLSVM, and VGAN-IDS procedures for providing reactive data transmission against critical channel distortions. The procedures developed inside the sensor node initiated channel attribute evaluation functions, reactive channel activation functions, malicious event monitoring functions, and reactive channel estimator functions. The proposed novel functions and complex data analysis models guarantee the channel protection and reliable communication [56; 57; 58]. Consequently, the proposed DMCAP commits the reduction in the retransmission rate, time complexity, and routing delay as illustrated in Section 4 against the existing systems such as CRLR, OETN, and SMC. Consequently, the DMCAP saves overall network energy and lifetime under uncertain channel conditions [59]. However, the proposed DMCAP procedures are lacking lightweight encryption mechanisms to enable data confidentiality and channel masking facilities. Additionally, this proposed model was not evaluated for multiple sensor nodes applied in WUGSNs. These are considered as the limitations of this proposed article. In future, the secure DMCAP is estimated to be designed and implemented for WUGSNs. R.S. and S.S.; Conceptualization, R.S. and D.P.B. ; methodology, software, validation, P.M.S. and S.G.R. ; formal analysis, D.D. and V.D. ; investigation, resources, data curation, writing--original draft preparation, R.S.