optimization algorithm. This new method was inspired by the circular structures on the seafloor which are created by one of the pufferfish species (Torquigeneralbomaculosus). The basic parameters of the inventive method were determined by the parameters observed during the process of the circular structure of the pufferfish. The process of performing this natural phenomenon is detailed in this work. In addition, detailed information about the concept of optimization, development process and activity areas are given in the study. The performance of this proposed method, which is inspired by nature, has been compared with other methods used extensively in the literature.
Chapter 24 proposes a hybrid optimization approach called HGWOSSO based on the integration of two swarm-based approaches, namely grey wolf optimizer (GWO) and sperm swarm optimization (SSO). The aim ofthis hybridization is to merge and enhance the capabilities of exploitation and exploration in both SSO and GWO to generate both in varied strengths. The functions of fixed-dimension multimodal, multimodal, and unimodal benchmarks gleaned from the literature are utilized to check the solution quality and performance of the HGWOSSO variant. The results revealed that the local search in SSO increases the ability of the hybrid variant in solving the benchmark functions, which significantly outperforms the GWO variant in terms of quality of solutions and capability of reaching the global optimum.
Chapter 25 envisions accessible lines of research associated with metaheuristics and highlights less explored areas of considerable concern. The authors concentrate on other metaheuristic approaches, hybrid processes, parallel metaheuristics, metaheuristics under uncertainty and multi-objective optimization. A review of these methods shows that while they are linked to several works, they have not been thoroughly investigated, and there are several open lines of study. The work considered in this chapter is especially beneficial for those researchers looking for novel fields in metaheuristics for multi-objective research and multi-objective optimization.
Chapter 26 deals with the issue of order reduction and controller synthesis in a unified domain for the PMSM drive. Two basic algorithms, viz. the firefly technique and the bacterial foraging optimization technique, are integrated to constitute a new topology known as the hybrid firefly algorithm (HFA). Originally, a PMSM drive consisting of both speed and current controllers created a higher-order system that has been reduced to a lower-order model via an identification method used in signal processing technology. In cascade control with a PI controller, the reduced-order model is there upon compared with that of the reference plant to roughly assess the unknown three-term controller parameters. The control parameters in the unified domain resemble almost accurately the continuous-time parameters at a low sampling limit. A unified controller design framework is thus developed for the drive. The smart algorithm is therefore successfully used both for the order reduction and for the estimation of the controller parameter of PMSM drives.
Chapter 27 presents the three-diode model-based PV module. The Harris hawks’ optimization (HHO) algorithm is used to estimate all the nine parameters of the system for three types of commercially available PV modules; namely, KC200GT multi-crystal, CS6K-280M mono-crystalline, STM6 40-36 mono-crystalline, Pro. SW255 poly-crystalline. The competitive and statistical experimental results show that HHO is advantageous in the sense that the sum of square error is lower as compared to that with other wellknown algorithms. The suggested technique also exhibits better convergence than the salp swarm algorithm (SSA), grey wolf optimizer (GWO), sine cosine algorithm (SCA), and dragonfly algorithm (DA).
Part IV: Sustainable Computing
Chapter 28 proposes a probability density function (PDF) optimized quantization (OQ) scheme for decision statistics at secondary user (SU) nodes to reduce communication overhead through the control channel in IoT cognitive radio network. A proposed approach was evaluated using software defined radio (SDR) setup consisting of RTL-SDR and Raspberry Pi (RPI). Using real-world signal, the proposed quantization strategy was tested with traditional soft-fusion, K-means clustering (KMC) and support vector machine (SVM)-based classifiers at the fusion center (FC). The results show a significant savings in bit requirement at FC to obtain an equivalent performance in comparison to similar schemes in the literature.
Chapter 29 describes recent advancements in energy-saving practices and strategies for achieving a strong vision of green IoT-enabled smart farming coupled with machine learning provided with prediction intelligence. A G-IoT prototype is formulated using machine learning to determine the outline of irrigation conditional nonlinear weather changes. The core aspect of this review article consists of surveys and discussions of the vital topics in green IoT-based smart farming and their enabler technologies.
Chapter 30 proposes a disseminated equal preparation structure for online content examination to proficiently deal with vast amounts of information. This model speaks to semantic content rundown from electronic information with the assistance of a frequent pattern tree and semantic metaphysics by utilizing the space information semantic. Here, MapReduce structure is utilized as information and text information is spoken of as slant term grid with numerical qualities. Results are provided to establish the proposed efficient sentiment analysis method. This method is capable of handling large web-based data efficiently and also performs well for handling synonyms.
Chapter 31 devises a three-phase system using fuzzy logic for node deployment and inter-node data transmission using the A* algorithm for analyzing crop-related data in precision farming. The model shows faster data coverage with fewer iterations than existing models along with a cost-effective optimized deployment strategy, which will help users save money and have access to proper real-time data. The result analysis is shown in accordance with the real-time deployment scheme.
Chapter 32 focuses on smart and precise agriculture to achieve better crop yields. The authors include several essential categories of the agricultural domain and highlight the importance of every category. Many different technologies are implemented to enhance crop yield, food security and ease of work. Artificial intelligence, internet of things, and robotics are discussed. These technologies help farmers at every crop stage—from showing to harvesting the crop, from packing to transportation. Artificial intelligence helps farmers utilize assets more economically and get fair use of farmland.
Chapter 33 discusses the developing needs of both academicians and professionals for understanding the relationship of various sustainable green initiatives, advanced manufacturing techniques, maintenance techniques and performance attributes. In this admiration, notwithstanding exhibiting the most recent understanding of the present status of the impact of four capacities on execution of vehicles organizations, it has valuable ramifications for managers with respect to the technique development.
Part V: AI in Healthcare
Chapter 34 utilizes the Bayesian paradigm in understanding the association between the gender and lipid profile among coronary artery disease (CAD) patients and compares the results with classical approaches. The research is based on the secondary analysis of data (n=1045) from a National Health and Nutrition Examination Survey (NHANES) (2015–2016) of individuals older than 50 years in which measures of the lipid profile were available. The clinical diagnosis of CAD was positive in 91 individuals. The comparison of differences in the lipid profiles across gender was performed under the classical (independent sample t-test) and Bayesian paradigm. Males positive for CAD were younger (54-80) than females (57-80). The lipid parameters (total cholesterol, LDL, Direct HDL, non-HDL) differed significantly across gender under both paradigms, except for triglyceride and two ratios (TC:HDL,