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To enhance the performance of the diffusion robust adaptive filtering algorithm, this paper presents a novel loss function framework named the "Tanh cost function framework." By utilizing this framework, we are able to incorporate standard cost functions, devise novel cost functions, and introduce the associated diffusion algorithm. Moreover, the convergence of the algorithm is thoroughly analyzed. Furthermore, the proposed diffusion Tanh algorithm family is simulated in a system identification model to assess its performance, demonstrating superior performance compared to the standard diffusive algorithm. Notably, the DTHLMS within the diffusion tanh algorithm family exhibits superior performance over the mainstream robust diffusion algorithms. [ABSTRACT FROM AUTHOR]

This article used an improved version of the Flow Direction Algorithm (FDA) with acceleration coefficients named Modified Flow Direction Algorithm (MFDA) for simultaneous Optimal Network Reconfiguration (ONR) and Optimal Distribution Generation's (ODG) installation to reduce the Active Power Losses (APL), maximize the Voltage Profile (VP) and stability of the Distribution System (DS). FDA is motivated by the simulation of the direction of water flow into a drainage basin at a lower elevation area. The neighboring flow and its slope also affect the direction of the water flow; its slope was obtained using the D8 method. FDA has a low convergence rate, stuck with local optima. This article proposed acceleration coefficients to acquire the proper balance between exploration and exploitation, accelerate the global convergence rate, and avoid getting stuck with local optima. The efficiency of the MFDA is evaluated based on its performance on 16 standard benchmark functions and is also used to solve the simultaneous ONR and ODG installation. Two DSs consisting of 33 and 69 bus test systems are considered to solve the problem. There are three methodologies to reduce the APL and maximize the VP and stability: ONR, ODG, and simultaneous ONR and ODG installation. This article uses four case studies with different load levels to show the proposed method's reliability. The analysis shows a better way to minimize the power loss by solving simultaneous ONR and ODG installation rather than only optimizing reconfiguration or installation of DG. It has been discovered that the results achieved are superior to those produced using the ISCA, FWA, HSA, etc. So, the MFDA shown can be a potentially useful way to solve 16 standard benchmark functions and simultaneous ONR and ODG installation. [ABSTRACT FROM AUTHOR]

This paper proposes a hybrid metaheuristic approach to optimize a duty cycle framework based on Seagull and Mayfly Optimization (HSMO-DC) Algorithm. This approach becomes crucial as current clustering protocols are unable to efficiently tune the clustering parameters in accordance to the diversification of varying WSNs. The proposed HSMO-DC primarily has two parts, where the first part takes care of the online cluster head selection and network communication using the seagull algorithm while the second part performs parameter optimization using the mayfly algorithm. The seagull is aimed at improving the energy distribution in the network through an effective bandwidth allocation procedure while reducing the total energy dissipation. Comparatively, with other clustering protocols, our proposed methods reveal an enhanced network lifetime with an improved network throughput and adaptability based on selected standard metric of performance measurement. [ABSTRACT FROM AUTHOR]