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    A reduced rule-based expert system by the simplification of logic functions for determining the life expectancy of intensive care patients
    (Emerald Group Publishing Ltd, 2017) Cizmeci, Inayet Hakki; Basciftci, Fatih
    Purpose - Specialist physicians, specialist nurses and personnel in the intensive care unit (ICU) work to treat patients. Compared with other hospital units, ICUs are full-fledged and provide 24-h services. However, patients are admitted to this unit because of conditions such as severe trauma, organ failure or dysfunction and poisoning. The life expectancy of such patients is considerably low. Design/methodology/approach - This study developed a reduced rule-based expert system to determine life expectancy. The purpose of this study is to determine the life expectancy of patients using ten variables. The rules were determined by evaluating 210 = 1,024 results. These rules were minimized using Boolean rules for simplification. Findings - Conclusions were drawn by evaluating the minimized cases rather than evaluating 1,024 different cases. ICU patients were evaluated using this method, and the mean success rate was 63.75 per cent. Originality/value - No rule-based expert system has been designed to determine the death risks of patients in the ICU.
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    Estimation of the Angles of a Robotic Arm with 7-Free Degrees Using an Improved Hybrid ESSA Algorithm
    (Wiley, 2023) Cizmeci, Inayet Hakki; Altun, Adem Alpaslan
    The electro-search algorithm (ESO) encounters challenges arising from its slow convergence rate and propensity to descend into local optima. In this study, a hybrid variant based on simulated annealing (SA), termed electro search simulated annealing (ESSA), is proposed to tackle these issues and surmount the obstacles. SA assists the proposed ESSA in escaping local optima through the cooling process while propelling individuals within the population. As these propelled individuals search for new positions, they engage in exploration and consequently approach the global optimum. This establishes a balance between exploitation and exploration for ESSA. ESSA has been compared with 10 metaheuristic algorithms on 15 benchmark functions with dimensions of 100, 500, and 1,000. The experimental results demonstrate its high-solution accuracy. Moreover, ESSA has been tested in the optimization of a robotic arm, a technology that requires low-error rates in the medical field. The analysis reveals the competitiveness and advantages of the proposed ESSA algorithm.
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    Improved Electro Search Algorithm with Intelligent Controller Control System: ESPID Algorithm
    (Tech Science Press, 2023) Cizmeci, Inayet Hakki; Altun, Adem Alpaslan
    Studies have established that hybrid models outperform single models. The particle swarm algorithm (PSO)-based PID (proportional-integral-derivative) controller control system is used in this study to determine the parameters that directly impact the speed and performance of the Electro Search (ESO) algorithm to obtain the global optimum point. ESPID algorithm was created by integrating this system with the ESO algorithm. The improved ESPID algorithm has been applied to 7 multi-modal benchmark test functions. The acquired results were compared to those derived using the ESO, PSO, Atom Search Optimization (ASO), and Vector Space Model (VSM) algorithms. As a consequence, it was determined that the ESPID algorithm's mean score was superior in all functions. Additionally, while comparing the mean duration value and standard deviations, it is observed that it is faster than the ESO algorithm and produces more accurate results than other algorithms. ESPID algorithm has been used for the least cost problem in the production of pressure vessels, which is one of the real-life problems. Statistical results were compared with ESO, Genetic algorithm and ASO. ESPID was found to be superior to other methods with the least production cost value of 5885.452.