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In this paper, we present a new neural network-based algorithm, KORA (Khalid ShadOw Replacement Algorithm), that uses backpropagation neural network (BPNN) for the purpose of guiding the line/block replacement decisions in cache. This work is a continuation of our previous research presented in [1]-[3]. The KORA algorithm attempts to approximate the replacement decisions made by the optimal scheme (OPT). The key to our algorithm is to identify and subsequently discard the dead lines in cache memories. This allows our algorithm to provide better cache performance as compared to the conventional LRU (Least Recently Used), MRU (Most Recently Used), and FIFO (First In First Out) replacement policies. Extensive trace-driven simulations were performed for 30 different cache configurations using different SPEC (Standard Performance Evaluation Corp.) programs. Simulation results have shown that KORA can provide substantial improvement in the miss ratio over the conventional algorithms. Our work opens new dimensions for research in the development of new and improved page replacement schemes for virtual memory systems and disk caches.